# Patent

## Title
Method for improving visualization of infrared images

## Abstract

A coding process applicable to an original infrared image, generated from any value matrix, to change the infrared image into negative or inverted black and white and grey with the addition of specific split colors, causing a substantial difference in the way the retina and the brain processes the resultant images. The result obtained is a much less exhaustive way to see, identify and interpret infrared images generated by any infrared camera that uses this conversion process.

## Background
CROSS-REFERENCE TO RELATED APPLICATIONS
This application is a continuation-in-part of U.S. Ser. No. 11/722,711 with a 371(c) date of Jun. 23, 2007, now pending, which is a National Phase entry Application of International Patent. Application No. PCT/BR2005/000201 with an international filing date of Sep. 22, 2005, designating the United States, and further claims priority benefits to Brazilian Patent Application No. MU 8403235-9, filed Dec. 24, 2004. The contents of all of these specifications, including any intervening amendments thereto, are incorporated herein by reference.


INCORPORATION BY REFERENCE OF MATERIAL SUBMITTED ON A COMPACT DISC
Tables 8 and 9 are provided on one compact disc. The compact disc contains two files named “Table 8.txt” and “Table 9.txt” The files were created on Nov. 13, 2010, and their size is 387,299 bytes and 387,046 bytes, respectively. The contents of the compact disc are hereby incorporated by reference in its entirety. 







LENGTHY TABLES




The patent contains a lengthy table section. A copy of the table is available in electronic form from the USPTO web site (http://seqdata.uspto.gov/?pageRequest=docDetail&DocID=US08520944B2). An electronic copy of the table will also be available from the USPTO upon request and payment of the fee set forth in 37 CFR 1.19(b)(3).






BACKGROUND OF THE INVENTION
1. Field of the Invention
The invention relates to a coding process for original infrared images, wherein the images are converted to negative black and white and wherein specific split colors are added causing a substantial difference in the way the retina and brain process the resultant images. The process allows for improved discrimination and interpretation of thermal content of infrared images and for easier understanding and perceiving of information contained in infrared images. Reading of infrared images coded using the process is much less tiring to the operator of thermal cameras and related software relative to original infrared images.
2. Description of the Related Art
Infrared thermography has been in development for over 50 years and significant advances have been made in the area of sensors, cooling, portability, weight, and ergonomics of infrared apparatus. The main purpose of these developments was to construct infrared apparatus that is more suitable and ergonomic for portable use and applicable to a wider array of applications. However, while much progress has been made in the realm of infrared hardware, visualization of thermal infrared images has largely been left behind and interpreting infrared images still presents a challenge.
Images produced by infrared thermographic equipments are alien to the human brain and cognitive process since our eyes perceives only the visible light range out of the entire electromagnetic spectrum. Chemical processes inside the human eye and functional cells distributions as well as cognitive-perceptual impact of images are a crucial part in the perception, detection, understanding and recording of infrared images. This invention alleviates the challenge of interpreting infrared images by processing raw infrared images so as to make them much more suitable for the human eye and mind.
In general, unprocessed infrared images are produced by infrared cameras, shown in FIG. 1, and described, e.g., in U.S. Pat. Nos. 5,420,419, 6,144,031, and D 483,782, which are designed to detect infrared radiation emitted by any object and transform these information into human-eye-recognizable images, making them possible to be interpreted in any specific situation.
Being so, all images produced by infrared cameras, digital or analog, are detected by an electronic sensor made from tiny cells called pixels, varying from 1 (one) to thousands or even millions, according to the camera capabilities (FIG. 2). After several electronic internal operations, the infrared radiation sensed by these pixels is coded to a matrix (Table 1) that is generated by electronic circuitry (FIG. 3) or other methods. Each value in Table 1 corresponds to incident radiation registered by a specific pixel of the sensor converted to a final value representing the adjusted temperature of the subject. U.S. Pat. No. 5,420,419 to Wood shows an example of an infrared camera employing this type of sensor.







TABLE 1





Sample value matrix





























. . .
. . .
. . .
. . .
. . .
. . .
. . .
. . .
. . .
. . .
. . .
. . .
. . .
. . .
. . .


. . .
45.00
45.00
44.80
44.60
44.30
44.10
43.60
43.30
43.30
42.60
40.50
37.90
36.70
. . .


. . .
45.00
44.90
45.10
45.20
45.20
45.10
44.70
44.70
44.60
44.60
44.00
42.20
40.70
. . .


. . .
44.90
45.30
45.60
46.00
46.10
46.00
45.60
45.60
45.20
44.40
43.40
43.20
42.00
. . .


. . .
45.00
45.50
45.80
46.20
46.50
46.30
45.90
46.10
46.60
46.30
45.90
44.90
41.90
. . .


. . .
44.50
44.90
45.50
46.00
46.00
45.90
45.90
46.50
47.60
48.10
47.70
46.50
42.50
. . .


. . .
43.00
43.90
44.50
44.90
45.70
46.90
47.70
48.30
48.70
48.80
49.00
48.20
45.90
. . .


. . .
44.80
45.40
45.90
46.80
47.40
48.60
49.30
49.50
49.60
49.70
50.00
49.60
48.30
. . .


. . .
45.60
45.80
45.70
46.10
48.00
49.20
50.10
50.50
50.80
50.90
51.10
50.80
49.90
. . .


. . .
46.00
46.40
47.40
48.00
49.50
50.60
51.00
51.70
52.20
52.30
52.50
52.10
51.30
. . .


. . .
47.40
48.00
49.30
50.10
51.30
52.00
53.00
53.70
54.00
54.40
54.40
54.00
53.30
. . .


. . .
48.60
49.50
50.50
51.30
52.50
53.80
55.00
55.90
56.30
56.60
56.70
56.40
55.70
. . .


. . .
49.30
50.90
51.70
52.90
54.50
55.90
57.10
58.20
58.90
59.70
60.30
60.50
60.10
. . .


. . .
49.90
52.20
53.60
54.80
56.20
57.50
59.00
61.30
65.10
67.10
68.40
68.90
68.60
. . .


. . .
50.70
53.30
55.10
56.80
58.80
61.40
64.80
68.30
71.20
74.30
76.30
77.50
77.50
. . .


. . .
52.30
54.40
56.60
59.80
65.80
69.70
72.00
74.90
77.90
81.20
83.50
85.20
86.00
. . .


. . .
53.70
56.20
61.50
67.00
71.20
74.70
78.00
81.50
84.70
87.90
90.90
92.90
94.20
. . .


. . .
55.20
60.90
67.10
71.10
74.40
78.90
82.10
86.10
90.10
93.90
97.00
99.00
100.60
. . .


. . .
57.80
65.10
70.10
72.80
77.40
81.90
85.20
88.40
93.80
98.80
101.90
104.10
105.70
. . .


. . .
61.30
66.10
70.80
75.90
80.00
83.00
85.90
92.30
99.60
104.00
106.70
108.40
109.50
. . .


. . .
64.30
68.10
72.30
77.20
82.00
86.40
92.70
100.20
105.60
108.50
110.10
111.40
112.30
. . .


. . .
66.30
70.30
74.50
79.90
86.90
94.70
100.90
106.30
109.80
111.50
112.40
113.10
114.30
. . .


. . .
67.90
70.40
73.50
80.20
92.00
101.70
106.90
110.20
112.90
115.10
115.70
115.40
114.50
. . .


. . .
70.00
72.80
74.40
80.40
96.10
105.60
109.90
113.20
115.20
117.60
118.80
117.50
109.30
. . .


. . .
71.50
74.60
75.50
84.70
100.30
108.70
112.10
115.40
117.80
119.00
118.60
111.70
94.40
. . .


. . .
71.70
73.60
76.50
91.10
105.30
112.00
114.40
116.60
119.30
120.00
113.30
95.70
74.20
. . .


. . .
71.60
72.90
80.90
96.40
108.60
114.20
116.50
117.90
117.10
114.70
99.80
75.90
59.00
. . .


. . .
71.10
72.70
84.00
100.00
110.70
115.60
118.20
118.90
114.30
100.90
79.30
59.20
51.30
. . .


. . .
70.80
72.50
85.10
101.40
112.20
116.70
119.30
120.10
113.70
92.30
65.80
51.50
48.70
. . .


. . .
. . .
. . .
. . .
. . .
. . .
. . .
. . .
. . .
. . .
. . .
. . .
. . .
. . .
. . .


. . .
69.10
69.40
85.90
104.00
113.00
116.20
116.00
110.40
93.70
71.70
56.90
49.80
47.70
. . .


. . .
69.10
70.60
86.10
103.50
112.50
115.20
113.00
101.30
81.40
63.20
54.90
50.80
48.30
. . .


. . .
70.00
70.00
86.30
103.40
111.90
114.60
109.90
93.60
72.20
58.60
53.60
51.80
49.80
. . .









This final matrix was obtained and decoded by a calibrated internal firmware or software to correspond to actual temperatures of the aimed at objects. Several correction factors built in the factory and adjusted in the field are included in these values. These processed values are then mounted to form electronic images, contained between the technical camera limits, independent on the camera type or model with which they were produced, and also independent of the observed object type, mechanical, electrical, masonry, plastic, organic, biological, or live organism etc. These built images can be presented in black, white and gray, or converted automatically to a false color scale.
Irrespective of electronic circuitry and internal software used or developed by any manufacturer, the entire infrared information is translated to a visual format that can be recognized by the human eye for neural and cognitive processing. The purpose of usual processing software or firmware applied to these images is to transform this values matrix in different black and white or false color tones that are more or less identifiable by the human eye whereby making the identification of regions of increased or lowered temperatures easier as can be seen in the two mugs shown in FIGS. 4a and 4b.
Another typical commercial software conversion changes the original values matrix or “black and white” images produced by the electronic circuitry and resident software to specific color arrangements producing false color images as shown in FIGS. 5a-c. This is done in order to attempt to build more suitable images for the human retina since its middle region is more capable to see in colors than in black and white due our biological retina cell structure called cones and rods. The result of conventional processing can be seen also in FIGS. 8a, 8b and 8c, and is explained in detail below. However, the final results obtained are poor and analyzing them is tiring to the human eye and brain leading the infrared camera operators to become easily tired and to commit more errors. Such errors lead to large financial losses.
Actually commercially available color coding processes applied on any infrared image lack the precision mixing for many colors and negatively impact the truly important technical information available to the user, mainly when the temperature differences are not so expressive. This happens because the black and white rod and color cones of human retina are not mimicked or emulated by the commercial color arrangements available on the market. The actually commercially available infrared false colored images are saturated with colors and lack precision and discrimination for a comfortable and clear and economic productive diagnosis of infrared image contents.
SUMMARY OF THE INVENTION
This invention relates to a process for converting the traditional thermal images visual presentation into a much more suitable visual format for the human eye and brain. The images are converted to negative black and white and specific split colors are added causing a substantial difference in the way the retina and brain processes the resultant images. This method reduces significantly the eye fatigue during the work day, increases the technician perception and makes the interpreting mental process a lot easier since the hottest part of the image, usually the most important, is clearly enhanced by the proper mixing of inverted black and white tones and color ones.



BRIEF DESCRIPTION OF THE DRAWINGS
The patent or application file contains at least one drawing executed in color. Copies of this patent or patent application publication with color drawing(s) will be provided by the Office upon request and payment of the necessary fee.
FIG. 1 shows a schematic representation of infrared radiation entering an infrared camera;
FIG. 2 shows an example of a part of an electronic sensor matrix of an infrared camera;
FIG. 3 shows a general schematic of the lenses and detector electronic circuitry that generates the infrared values matrix;
FIG. 4a shows visible light image of two mugs one with hot and one with cool water inside;
FIG. 4b shows a simple black and white infrared image of the mugs in FIG. 4a wherein brighter tones are related to hotter areas on the mugs and darker tones to colder areas;
FIGS. 5a-c show three actual commercial false color infrared images of the mugs in FIG. 4a;
FIG. 6 shows eighteen different examples of different colors mixed with inverted black and white tones arrangements assigned to the same specific temperature range (0° C. to 100° C.);
FIG. 7 shows an exemplary of the same color scheme assigned to different temperature ranges;
FIG. 8a shows the distribution of cones and rods on the retina being the fovea the central posterior point of the eye (Osterberg, 1935. See also Hecht, Eugene, Optics, 2nd Ed, Addison Wesley, 1987);
FIG. 8b shows a schematic diagram of the human retina, enhancing the cones (RGB sensor cells) and cones (B&W sensor cells);
FIG. 8c shows the cones and rods concentration distribution as seen through the direct axis of the eye;
FIG. 9 shows unprocessed basic original (black and white) infrared images. All images were subjected to the same thermal adjustments and limits. (The whiter the image area the hotter it is);
FIG. 10 shows processed infrared images processed using commercial false color “iron” scheme. All images were subjected to the same thermal adjustments and limits. (The yellower the image area the hotter it is);
FIG. 11 shows processed infrared images processed using commercial false color “rainbow” color scheme. All images were subjected to the same thermal adjustments and limits. (The whiter the image area the hotter it is);
FIG. 12 shows processed infrared images processed using an exemplary embodiment of the invention. The images were converted from infrared to inverted back-and-white (X-ray) with false color split added. All images were submitted to the same thermal adjustments and limits. (The whiter the image area the, hotter it is);
FIG. 13 shows a common black and white thermal image of an oven;
FIG. 14 shows a good quality adjustment thermal image of the FIG. 13 oven at between 15 and 30° C.;
FIG. 15 shows a bad quality adjustment thermal image of the FIG. 13 oven at between 0 and 200° C.;
FIG. 16a shows a thermal image of an oven with actual commercial “iron” false colors schemes added;
FIG. 16b shows a thermal image of an oven with actual commercial “rainbow” false colors schemes added;
FIG. 17 shows a thermal image of an oven using an exemplary embodiment of the invention. The image was converted from infrared to inverted back-and-white (X-ray) with false color split added;
FIG. 18 shows the color RGB 103 103 103;
FIG. 19 shows an exemplary hot spot at 27.5° C.;
FIG. 20 shows the color RGB 95 189 206;
FIG. 21 shows a zoomed in area of the oven hot spot in FIG. 19;
FIG. 22 shows a thermal image of a high tension terminal with the actual invention colors with inverted black and white tones applied;
FIG. 23a shows a hotspot selected in FIG. 22 for the purpose of demonstrating how the coding calculations are done;
FIG. 23b shows a zoomed part of FIG. 22 to enhance the hotspot;
FIG. 24 shows the hotspot RGB color code and correlated color of the hotspot selected in FIG. 23a;
FIG. 25 shows a zoom of the hotspot area to demonstrate the color of FIG. 24;
FIGS. 26a and 26b show the consecutive RGB color lines result from both calculations from the top and bottom reference temperatures;
FIG. 27 shows visible light image of metal objects illustrating the principle that the warmer the temperature of portions of the objects, the whiter the light emitted by those portions; and
FIGS. 28a-d show acomparative effect of applying twice the X-ray effect to the same thermal image, wherein duing the step of mixing the color tones and the black and white tones into a single image, more than one set of the black and white tones are applied to the image for image enhancing purposes.



DETAILED DESCRIPTION OF THE INVENTION
This application relates to a new coding process for infrared images, which are generated from a temperature values matrix obtained from an electronic infrared sensitive circuitry and coded to a generic false color (usually the commercial, most used and known as iron or rainbow or black and white) pattern. By the use of the method of the invention, the images are coded into a negative black and white pattern with a soft color split separation whereby producing a large visualization contrast of parts or sectors of the registered infrared image object indicating critical or important temperature changes.
The present technical process transforms the basic output visual information produced by the infrared cameras, either by an analog matrix or digital files, using a specific mixing with false colors and black and white palettes mixed in such a way that the final infrared image is presented integrating smoothly a negative black and white visual image with balanced color tones producing a large discrimination effect. This optimum result is due to the fact that the total color scheme of the final images mimics the human retina. Also, the images processed by this technique mimic the photographic X-ray effect that provides a standardized way of viewing, is universally and easily recognizable, and includes different color scales attached to different temperature levels.
There is a large advantage to using the photographic X-ray effect because it uses the photographically well known black and white and grey tones to invert images. In this context the “inverted” black and white refers old “negative” photographic films. In the old films “black” in the negative chemical film means brighter on the photo (or photographic paper) and “white” means darker due the effect this tones produces when “revealed” or “turned” to photographic paper. As X-rays are still used today and make use of this traditional inversion effect, it is very easy to understand what the content information of the image is. There is no difference to the human retina, but to interpret or understand the images content, it is an easy and worldwide-recognized format.
In a particular embodiment, this technique involves the utilization of a single color scale for all the processed images that is poorly effective when used to understand the information contained in the image.
Since the infrared radiation emitted by the subject hits a pixel of the sensor, with a resultant electrical or digital value of it attributed to every sensor pixel, then being calibrated and correlated in factory to represent the actual temperature of the subject, it is feasible to code this values to a color RGB (Red, Green and Blue) arrangement, such that the human eye and brains cognitive processing results in a very clear and understandable visual image. To split a visible light into its fundamental components red (R) green (G) and blue (B) is a well know physical principle, known as visual light decomposing in its fundamental colors, and is the standard way to manage visual light composing electronic systems. There are several color arrangements that can be utilized always following the general rule of mixing specific high contrast colors and an inverted or not-inverted black white and gray portion of the entire image. FIG. 6 shows several examples of these possible schemes. All of them apply the same general principle and rule of creating an X-ray type image mixed with false colors that is the embodiment of this invention. A particular black and white distribution case can be seen in FIG. 6 second line, first scale from the left to right, and third line, third and fourth scales from left to right where the black and white portion of the scale is repeated twice. The final result of this particular arrangement can be seen in FIGS. 28a-d where the X-ray type effect is still retained.
As can be seen in FIG. 6, a large quantity of different color arrangements is possible. Also, as the lower and upper temperature limits of each image can be calibrated on the very camera, the color schemes must only be correlated proportionally to the maximum and minimum displayed temperatures, independent of the particular software, firmware or electronic circuitry adopted to produce the infrared images. This can be applied to any manufacturer or infrared or system camera as any infrared camera video output will always have to be optimized to the human eye response to color and black and white tones.
Also, the same process can be applied to any temperature range as can be seen in FIG. 7. It can be noted easily that the color distribution scheme generated by this technique is the same, but that the limit temperature ranges varies among others from −42.3° C. to −2° C., from −7.6° C. to 136° C., and from 236.1° C. to 1,383.5° C. This coding system is sufficiently flexible to be used with any temperature range.
According to this invention, any infrared camera, regardless of the specific electronic circuitry architecture it employs, or any internal software or firmware, has to produce a final visual video signal output that passes through a code processing or algorithm to convert the original infrared—invisible to the human eye—signal in a colored one—visible to the human eye. This application refers to a universal solution that is independent of the camera type, camera circuitry, camera firmware or software, or post-processing software for treatment of the original images, or even the temperature limits, and is not being limited by any of these factors.
An illustrative example of a generic temperature pixel correlation that enables this image transformation is shown in Table 2. This table shows RGB values that are associated with particular temperature values generated by any infrared camera This table refers to RGB codes that are applied to an image that starts at 0° C. and goes to 500° C. There are 256 code lines in this example for the number 256 is a typical multiple of the 8 bit words and it is common knowledge that every image pixel of infrared information can be translated in 8 bits per color, or 256 color shades per pixel. This makes it possible to represent a visual output with about 16.7 millions of different color and that makes the 256 color systems very common and used too in several visible light image data processing files.
In any event, the total number of color lines will vary according the hardware and software capacity and infrared camera design. For example, older cameras can only manage 120 color lines. Also, the number of colors is not limited; the more colors or lines are used, the softer the image will be. In Table 2, the lines are numbered for demonstration purposes and every temperature related to each line is identified at the right column. Then using RGB codes, the original infrared matrix values are translated electronically to colors and presented on the thermovision LCD, viewfinder or computer screen.







TABLE 2







RGB Values Associated with Particular Temperature Values














LINE
R
G
B
COLOR
TEMP.


















1
248
248
248
Almost
500° C.







White



2
248
248
248

498° C.



3
247
247
231

496° C.



4
246
246
214

494° C.



5
246
245
196

492° C.



6
245
244
179

490° C.



7
244
243
162

488° C.



8
243
241
145

486° C.



9
242
240
128

484° C.



10
242
239
110

482° C.



11
241
238
93

481° C.



12
240
237
76

479° C.



13
239
236
59

477° C.



14
239
228
74

475° C.



15
239
218
72

473° C.



16
238
209
70

471° C.



17
237
199
68

469° C.



18
237
190
66
Yellow
467° C.







Gold



19
236
181
64

465° C.



20
235
171
62

463° C.



21
235
162
60

461° C.



22
234
152
58

459° C.



23
233
143
56

457° C.



24
233
134
55

455° C.



25
232
124
53

453° C.



26
232
115
51

451° C.



27
231
105
49
Orange
449° C.



28
230
96
47

447° C.



29
230
87
45

445° C.



30
229
77
43

443° C.



31
228
68
41

442° C.



32
228
58
39

440° C.



33
227
49
37

438° C.



34
220
49
36

436° C.



35
214
50
36

434° C.



36
207
50
35

432° C.



37
201
50
34

430° C.



38
194
51
34

428° C.



39
188
51
33
Dark Red
426° C.



40
181
52
32

424° C.



41
175
52
32

422° C.



42
168
52
31

420° C.



43
161
53
30

418° C.



44
155
53
30

416° C.



45
148
53
29

414° C.



46
142
54
28

412° C.



47
135
54
27

410° C.



48
129
54
27

408° C.



49
122
55
26

406° C.



50
115
55
25

404° C.



51
109
55
25

403° C.



52
102
56
24
Brown
401° C.



53
96
56
23

399° C.



54
89
57
23

397° C.



55
83
57
22

395° C.



56
76
57
21

393° C.



57
70
58
21

391° C.



58
63
58
20

389° C.



59
60
63
26

387° C.



60
56
69
32

385° C.



61
53
74
38

383° C.



62
50
79
44

381° C.



63
47
84
49

379° C.



64
43
90
55

377° C.



65
40
95
61

375° C.



66
37
100
67
Dark Green
373° C.



67
33
106
73

371° C.



68
30
111
79

369° C.



69
34
115
86

367° C.



70
37
120
93

365° C.



71
41
124
100

364° C.



72
44
128
107

362° C.



73
48
133
114

360° C.



74
52
137
121

358° C.



75
55
141
128

356° C.



76
59
146
135

354° C.



77
62
150
142

352° C.



78
66
154
150

350° C.



79
70
159
157

348° C.



80
73
163
164

346° C.



81
77
168
171

344° C.



82
80
172
178
Light Blue
342° C.



83
84
176
185

340° C.



84
88
181
192

338° C.



85
91
185
199

336° C.



86
95
189
206

334° C.



87
98
194
213

332° C.



88
102
198
220

330° C.



89
99
192
217

328° C.



90
95
186
214

326° C.



91
92
180
211

325° C.



92
88
175
209

323° C.



93
85
169
206

321° C.



94
81
163
203

319° C.



95
78
157
200

317° C.



96
74
151
197

315° C.



97
71
145
194

313° C.



98
67
140
192

311° C.



99
64
134
189

309° C.



100
61
128
186

307° C.



101
57
122
183
Medium
305° C.







Blue



102
54
116
180

303° C.



103
50
110
177

301° C.



104
47
104
174

299° C.



105
43
99
172

297° C.



106
40
93
169

295° C.



107
36
87
166

293° C.



108
33
81
163

291° C.



109
32
77
155

289° C.



110
31
74
148

287° C.



111
30
70
140

286° C.



112
28
67
132

284° C.



113
27
63
125

282° C.



114
26
60
117

280° C.



115
25
56
109

278° C.



116
24
53
102

276° C.



117
23
49
94
Dark blue
274° C.



118
22
46
86

272° C.



119
20
42
79

270° C.



120
19
38
71

268° C.



121
18
35
64

266° C.



122
17
31
56

264° C.



123
16
28
48

262° C.



124
15
24
41

260° C.



125
13
21
33

258° C.



126
12
17
25

256° C.



127
11
14
18

254° C.



128
10
10
10
Black
252° C.



129
12
12
12

250° C.



130
13
13
13

248° C.



131
15
15
15

247° C.



132
17
17
17

245° C.



133
18
18
18

243° C.



134
20
20
20

241° C.



135
22
22
22

239° C.



136
23
23
23

237° C.



137
25
25
25

235° C.



138
27
27
27

233° C.



139
28
28
28

231° C.



140
30
30
30

229° C.



141
32
32
32

227° C.



142
34
34
34

225° C.



143
35
35
35

223° C.



144
37
37
37

221° C.



145
39
39
39

219° C.



146
40
40
40

217° C.



147
42
42
42

215° C.



148
44
44
44

213° C.



149
45
45
45

211° C.



150
47
47
47

209° C.



151
49
49
49

208° C.



152
50
50
50

206° C.



153
52
52
52

204° C.



154
54
54
54

202° C.



155
55
55
55

200° C.



156
57
57
57

198° C.



157
59
59
59

196° C.



158
60
60
60

194° C.



159
62
62
62

192° C.



160
64
64
64

190° C.



161
65
65
65

188° C.



162
67
67
67

186° C.



163
69
69
69

184° C.



164
70
70
70

182° C.



165
72
72
72

180° C.



166
74
74
74

178° C.



167
76
76
76

176° C.



168
77
77
77

174° C.



169
79
79
79

172° C.



170
81
81
81

170° C.



171
82
82
82

169° C.



172
84
84
84

167° C.



173
86
86
86

165° C.



174
87
87
87

163° C.



175
89
89
89

161° C.



176
91
91
91

159° C.



177
92
92
92

157° C.



178
94
94
94

155° C.



179
96
96
96

153° C.



180
97
97
97

151° C.



181
99
99
99
Dark Grey
149° C.



182
101
101
101

147° C.



183
102
102
102

145° C.



184
104
104
104

143° C.



185
106
106
106

141° C.



186
107
107
107

139° C.



187
109
109
109

137° C.



188
111
111
111

135° C.



189
112
112
112

133° C.



190
114
114
114

131° C.



191
116
116
116

130° C.



192
118
118
118

128° C.



193
119
119
119

126° C.



194
121
121
121

124° C.



195
123
123
123

122° C.



196
124
124
124

120° C.



197
126
126
126

118° C.



198
128
128
128

116° C.



199
129
129
129

114° C.



200
131
131
131

112° C.



201
133
133
133

110° C.



202
134
134
134

108° C.



203
136
136
136

106° C.



204
138
138
138

104° C.



205
139
139
139

102° C.



206
141
141
141

100° C.



207
143
143
143

 98° C.



208
144
144
144

 96° C.



209
146
146
146

 94° C.



210
148
148
148

 92° C.



211
149
149
149

 91° C.



212
151
151
151

 89° C.



213
153
153
153

 87° C.



214
154
154
154

 85° C.



215
156
156
156

 83° C.



216
158
158
158

 81° C.



217
160
160
160

 79° C.



218
161
161
161

 77° C.



219
163
163
163

 75° C.



220
165
165
165

 73° C.



221
166
166
166

 71° C.



222
168
168
168

 69° C.



223
170
170
170

 67° C.



224
171
171
171

 65° C.



225
173
173
173

 63° C.



226
175
175
175

 61° C.



227
176
176
176

 59° C.



228
178
178
178

 57° C.



229
180
180
180

 55° C.



230
181
181
181

 53° C.



231
183
183
183

 52° C.



232
185
185
185

 50° C.



233
186
186
186

 48° C.



234
188
188
188

 46° C.



235
190
190
190

 44° C.



236
191
191
191

 42° C.



237
193
193
193

 40° C.



238
195
195
195

 38° C.



239
196
196
196

 36° C.



240
198
198
198

 34° C.



241
200
200
200

 32° C.



242
202
202
202

 30° C.



243
203
203
203

 28° C.



244
205
205
205

 26° C.



245
207
207
207

 24° C.



246
208
208
208

 22° C.



247
210
210
210

 20° C.



248
212
212
212

 18° C.



249
213
213
213

 16° C.



250
215
215
215

 14° C.



251
217
217
217

 13° C.



252
218
218
218

 11° C.



253
220
220
220

 9° C.



254
220
220
220

 7° C.



255
200
200
200

 5° C.



256
200
200
200
Light Gray
 3° C.










A fixed or constant temperature correlation to each and every RGB code is not necessary since in every image, the temperatures related to every RGB code will be different and will be set by any electronic circuitry that performs this invisible-infrared-to-visible-light visual conversion. All black-and-white and color RGB codes are divided and correlated by signal processing electronic circuitry, or in post-processing software to produce a proportional, linear or non-linear, or even completely inverted (inverted black-and-white AND colors) visual output. Different black, white, grey and color scales, the different colors proportions and densities applied to the infrared images permit greater levels of discrimination for any object or scenery at which an infrared camera is aimed. Also, the number of color combinations is actually unlimited, especially when added to black and white and grey intermediary tones. Some of these combinations are shown in FIG. 6.
It is important to note that all the temperature ranges shown in FIG. 6 are the same (50° C. to 100° C.) and that there are color examples with one or even two black-and-white inverted color tones. This demonstrates the main concept of this invention that is to use the color tones mixed with inverted black and white and grey tones to create an excellent discrimination on the infrared information converted to visible light and presented to the human eye and brain. This enhanced discrimination can be easily seen when comparing the effect of its application on FIGS. 10, 11 and 12 with FIG. 13.
The general algorithm for modifying infrared images includes softly splitting the image into two levels, without limitation. The vast majority applications will use first level from top to bottom, containing the colors to be interpreted following the intuitive meaning of colors; the “whiter” the tones, the warmer the spots seen by the infrared camera and the “blacker” or “darker” the tones, the colder the part of the thermal image. In the second level, the inverted black and white (mimicking or emulating the universally well known X-ray photographic films) part of the thermal image has the important function to create an environment reference using not meaningful temperatures. The X-ray part of the image will permit to locate precisely where the hot spot is, and to mentally discard the “non-important” temperatures, but will preserve the colored “important” ones, in this way creating a higher level of interpretational security with a lower visual, brain stress, as can clearly be seen in FIG. 12. The process of mixing of any color tones with the inverted black and white is the main factor that allows for the creation of visual comfort and increases the accuracy of the thermal image interpretation. It is not critical which color scale or proportion is used by the designer.
The main advantage of this new specific mixing process is the excellent characterization and easy localization of the interest points or spots. Due to palette division between inverted black white added to colors palettes, all reference areas are made clearer (explicit), wherein the color area represents the interest temperatures and the inverted black and white (in negative) areas gives the exact context localization of the interest area. Actual existing commercial color schemes applied to infrared images (e.g., “iron” or “rainbow”) do not utilize this division and result in a significantly poorer discrimination of any infrared image with a bigger eye and mental stress by the end of a working day. This can be seen in FIGS. 11 and 12.
The specific coding process described herein mimics the human eye retina characteristics making the images far more suitable to interpretation than those using only false colors. FIG. 8a shows a didatic horizontal cut of the eye and, just bellow it, a graphic showing the color sensors (cones) and black and white sensors (rods) distribution along the angles quoted in the schematic cut, above the curves. As can be seen on this graphic curves, the human retina has most of the color sensors (cones—red curve) located at the bottom of each eye (0° or fovea) and the black and white sensors (rods—black curve) located mainly spread through the sides of the retina (peak between 25° and)45° with respect to the fovea position. FIG. 8b shows the general schematic for the cones and rods distributions making it clear the different cones sensitives for RED, GREEN and BLUE (RGB) frequencies of the visible light. FIG. 8c shows the same FIG. 8a curve distribution between cones RGB and rods B&W but as if seen through the central eye axis.
There are about 6.5 to 7 million cones in each eye, and they are sensitive to bright light and to color. The highest concentration of cones is in the macula, a point near the middle rear of the eye globe retina. The fovea centralis, at the center of the macula, contains only cones and no rods. By the other side, there are about 120 to 130 million rods in each eye, and they are sensitive to dim light or presence of light or not (that translates to white or black tones), to movement, and to shapes. The higher concentration of rods is in the peripheral retina, decreasing in density up to the macula. It can be easily seen from the numbers above, that the rods or white and black cells are about 20 times greater than the cones or color cells in the retina. Also, the central point of the eye, the fovea is dedicated to color perception since it has no rods in it and the peripheral of the retina is dedicated to white and black tones (light presence or not). These are the reasons for why building an image mimicking this arrangement makes the image faster and easier to understand and decode and less tiring to the human eye and brain. As the original radiated infrared information is perceived neither by the human eye nor by the brain, it is difficult to interpret such images if they are built completely with false colors. Mimicking or emulating the sensors proportions of the human retina makes these images much more natural to see and interpret. They appear to the operators' eyes and brain much more clearly and more well defined than any images treated with false color schemes only.
FIGS. 9-21 illustrate this invention further. FIG. 9 shows common infrared images generated by common infrared cameras available on the market without using any specific software processing (so called, raw black-and-white infrared images). All images in FIGS. 9 to 12 were calibrated at the same adjustments. FIG. 10 shows common false color palette scheme (“iron”) applied to infrared images. FIG. 11 shows the same images processed using another false color palette scheme (“rainbow”). FIG. 12 shows the same images processed by software calibrated to apply color separation adding inverted black and white (negative film photographic or X-ray effect) to all the temperatures of the infrared image. The progression of figures shows how much simpler and clearer the images become when they are subjected to the methods described herein. The methods described herein can be applied to any image obtained from any thermal or infrared camera.
With specific reference to the “High Tension Terminal” thermal image shown in the lower left-hand corner in FIG. 9, electrical components suffering from certain problems are identified by higher temperature registered by an infrared camera. Except of the defective component, the rest of the image is presented on a homogeneous dark gray scale tone, or similar. The poor contrast that shows the thermal differences is produced by regular software available on the market that correlates brighter tones of gray, up to white, to hotter temperatures. Other usual color schemes applied to the same thermal image correlate colors such as red, yellow orange, green, blue or violet to the entire infrared image can be seen in FIGS. 10 and 11 with similar color saturation and poor discrimination. An increased discrimination quality of the same image, when the inverted black and white tones with split colors are applied, can be seen at FIG. 12.
The process according to this invention, by means of modifications introduced on any software or firmware that generates this type of image, mixes the black and white (inverted or non-inverted) codification for the parts of the objects that doesn't show important thermal differences and adds a specific color scheme to those parts that indicate an anomaly. The added colors contrast with the black and white (inverted or non-inverted) reference palette. This process “clarifies” significantly infrared images, making them a lot easier to understand and judge, increasing significantly the correct evaluations and lowering stress and fatigue associated with viewing infrared images.
Multiple anomalies can be seen with this processing that could not be clearly seen using other schemes, e.g., by changing the intensity and proportions of the color saturation. This can be seen comparing the images on FIGS. 9 to 11 with FIG. 12. Another benefit of this mixing process is to make more complex interpretations available to less trained technicians since the coding process enhances what should be looked for in an infrared image and its use is much simpler and easier than use of images which introduce false colors.
In addition, in many cases, a visible-light control image is no longer needed since the X-ray format makes the surroundings clearer than the false colors used conventionally. This allows ink and paper to be saved with evident ecological benefits. The specific digital and or electronic algorithms according to this invention that will be made available to every commercial camera, or firmware, or even post processing software will vary on the electronic or software language the manufacturer chooses to use to produce its cameras and software. Nevertheless to obtain the advantages of an excellent discrimination and resolution to any processed infrared image, a retina mimicking scheme of color with inverted black and white mixing shall be used, i.e., black-and-white tones will be mixed with high contrast colors.
EXAMPLES
Example 1
Grayscale Infrared Image
An infrared image of a kitchen oven was taken using a 320×240 pixel infrared sensor. The infrared image is shown in FIG. 13 without a temperature reference scale by its side. Every pixel of this image has a temperature value associated with it. Because of the large number of values obtained (320×240=76800), a partial listing is shown in Table 3. The complete listing is shown in Table 8, which is appended hereto on a compact disc. The file on the compact disc is labeled Table—8.txt. Although in this example, a 320×240 sensor size is used, this method is applicable for sensors of any sizes, bigger or smaller. In addition, although there are several parameters that can be adjusted to obtain the infrared image this image, such as optical focus, ambient temperature, optics temperature, target emissivity, wind speed (if any), reflected temperature and so on, this method is applicable to the final visual video output regardless whether such prior adjustments have or have not been made.







TABLE 3







Temperature Values of a Kitchen Oven as Measured by 320 × 240 pixel


Infrared Sensor (Partial Listing)









COLUMNS






















LINES
1
2
3
4
5
6
7
8
9
10
11
12
13
14
. . .

























1
21.4
21.4
21.5
21.5
21.6
21.5
21.4
21.4
21.5
21.5
21.5
21.3
21.4
21.3
. . .


2
21.5
21.5
21.5
21.5
21.5
21.5
21.5
21.3
21.5
21.3
21.3
21.5
21.3
21.3
. . .


3
21.5
21.5
21.6
21.6
21.6
21.5
21.5
21.6
21.6
21.5
21.7
21.6
21.4
21.5
. . .


4
21.5
21.4
21.5
21.6
21.6
21.7
21.8
21.6
21.7
21.4
21.3
21.4
21.3
21.2
. . .


5
21.3
21.5
21.5
21.6
21.6
21.6
21.6
21.5
21.5
21.4
21.2
21.6
21.4
21.1
. . .


6
21.5
21.5
21.8
21.6
21.9
21.8
21.6
21.6
21.7
21.6
21.5
21.5
21.6
21.6
. . .


7
21.5
21.6
21.8
21.6
21.8
21.6
21.6
21.6
21.6
21.6
21.6
21.6
21.3
21.5
. . .


8
21.5
21.5
21.8
21.5
21.7
21.6
21.6
21.7
21.8
21.8
21.5
21.7
21.5
21.5
. . .


9
21.5
21.6
21.6
21.7
22
21.6
21.6
21.5
21.8
21.8
21.4
21.5
21.5
21.3
. . .


10
21.6
21.6
21.6
21.8
21.8
21.6
21.6
21.7
21.6
21.8
21.7
21.7
21.5
21.5
. . .


11
21.9
21.7
21.7
21.9
21.8
21.8
21.8
21.6
21.7
21.9
21.5
21.6
21.6
21.5
. . .


12
21.7
21.7
21.6
21.8
21.7
21.9
21.5
21.7
21.8
21.9
21.7
21.6
21.5
21.5
. . .


13
21.5
21.5
21.6
21.7
21.9
21.9
21.8
21.8
21.9
21.8
21.8
21.5
21.4
21.6
. . .


14
21.5
21.6
21.6
21.6
21.8
21.9
21.7
21.8
21.8
21.8
21.8
21.6
21.4
21.4
. . .


15
21.6
21.7
21.8
21.8
21.8
21.9
21.7
21.7
21.8
21.8
21.8
21.8
21.6
21.6
. . .


16
21.6
21.6
21.5
21.9
21.9
21.6
21.5
21.7
21.6
21.6
21.6
21.5
21.6
21.5
. . .


17
21.5
21.7
21.6
21.8
21.9
21.6
21.8
21.7
21.8
21.7
21.5
21.5
21.5
21.6
. . .


18
21.5
21.6
21.6
21.9
22
21.9
21.8
21.7
21.7
21.8
21.6
21.9
21.5
21.5
. . .


19
21.9
21.6
21.6
21.9
21.9
21.8
21.8
21.7
21.8
21.8
21.7
21.8
21.7
21.5
. . .


20
21.5
21.6
21.8
21.8
21.8
21.9
21.7
21.8
21.8
21.7
21.8
21.7
21.5
21.6
. . .


21
21.5
21.7
21.7
21.8
21.9
21.8
21.8
21.9
21.8
21.8
21.8
21.8
21.6
21.6
. . .


22
21.6
21.6
21.7
21.9
21.9
21.7
21.7
21.8
21.8
21.6
21.9
21.8
21.6
21.6
. . .


23
21.7
21.6
21.6
21.9
21.9
21.9
21.9
21.6
21.8
21.7
21.7
21.5
21.8
21.6
. . .


24
21.8
21.6
21.7
21.8
22.1
21.9
21.9
21.8
21.9
21.8
21.7
21.8
21.8
21.6
. . .


25
21.5
21.6
21.6
21.6
21.8
21.8
21.8
21.8
21.7
21.9
21.8
21.7
21.6
21.6
. . .


26
21.5
21.4
21.8
21.8
21.9
22
21.9
21.9
21.8
21.8
21.8
21.6
21.8
21.7
. . .


27
21.6
21.7
21.6
21.9
22
21.8
21.7
21.8
21.8
21.6
21.7
21.7
21.6
21.6
. . .


28
21.6
21.7
21.7
21.9
22
21.9
21.7
21.9
21.8
21.9
21.6
21.5
21.6
21.6
. . .


29
21.5
21.6
21.8
21.9
21.7
21.8
21.8
21.8
21.8
21.6
21.3
21.5
21.3
21.5
. . .


30
21.6
21.6
21.9
21.8
21.8
21.9
21.7
21.7
21.6
21.6
21.2
21.4
21.5
21.6
. . .


31
21.6
21.6
21.7
21.9
22.1
21.9
21.6
21.9
21.7
21.5
21.4
21.5
21.6
21.7
. . .


32
21.5
21.6
21.9
21.9
22.2
22.1
21.8
21.8
21.6
21.5
21.5
21.5
21.6
21.8
. . .


33
21.7
21.6
21.9
22
21.9
21.8
22
21.9
21.8
21.3
21.3
21.4
21.4
21.8
. . .


34
21.7
21.6
21.9
22
22
22.1
21.9
21.6
21.7
21.7
21.5
21.3
21.5
21.5
. . .


35
21.6
21.7
22
22.1
22.1
22
21.9
22
21.8
21.8
21.4
21.3
21.5
21.8
. . .


36
21.5
21.8
21.6
22
22
22.1
22.2
21.9
21.8
21.6
21.4
21.6
21.5
21.7
. . .


37
21.5
21.7
21.8
21.9
22
22
22.1
21.9
21.9
21.5
21.4
21.4
21.7
21.7
. . .


38
21.8
21.7
21.9
21.9
22.3
22
22
21.9
21.8
21.7
21.3
21.4
21.3
21.6
. . .


39
21.6
21.7
22
21.8
22.1
22
21.9
22
21.8
21.6
21.3
21.4
21.4
21.5
. . .


40
21.6
21.7
21.8
22.1
22.3
22
21.9
21.8
21.8
21.7
21.3
21.4
21.6
21.6
. . .


41
21.5
21.8
22
22
22.2
22.2
22
22
21.9
21.6
21.4
21.5
21.6
21.8
. . .


42
21.7
21.7
22.1
22.2
22.2
22.3
22
22.1
22
21.9
21.5
21.5
21.7
21.5
. . .


43
21.6
21.7
21.9
22.2
22.3
22
22.2
21.9
22
21.8
21.5
21.5
21.5
21.7
. . .


44
21.6
21.8
21.9
22.3
22.2
22.3
22.1
22.1
22
21.8
21.5
21.6
21.7
21.8
. . .


45
21.8
21.7
22
22
22.3
22.3
22.2
22
21.9
21.9
21.6
21.5
21.7
21.8
. . .


46
21.6
21.7
21.8
22.1
22.3
22.3
22.3
22.1
22
21.9
21.6
21.6
21.6
21.9
. . .


47
21.7
21.9
21.9
22.3
22.3
22.3
22.3
22.1
22.1
21.8
21.6
21.4
21.8
21.6
. . .


48
21.7
21.8
21.8
22.2
22.4
22.2
22.3
22.1
22.1
21.9
21.4
21.4
21.6
21.8
. . .


49
21.8
21.9
21.9
22.2
22.4
22.3
22.3
22.2
22.1
21.9
21.6
21.6
21.6
21.7
. . .


50
21.6
21.9
21.8
22.2
22.4
22.3
22.1
22.1
22
21.9
21.5
21.6
21.7
21.5
. . .


51
21.7
21.8
22.1
22.4
22.6
22.4
22.2
22.1
22.1
21.9
21.6
21.5
21.5
21.7
. . .


52
21.7
22
21.9
22.2
22.5
22.4
22.3
22.2
22.2
22.1
22
21.8
21.6
21.6
. . .


53
21.6
21.8
21.9
22.1
22.3
22.4
22.3
22.1
22.3
22.2
22.1
21.9
21.6
21.6
. . .


54
21.5
21.8
21.9
21.9
22.3
22.4
22.1
22.2
22.1
22.1
22.2
22.1
21.6
21.5
. . .


. . .
. . .
. . .
. . .
. . .
. . .
. . .
. . .
. . .
. . .
. . .
. . .
. . .
. . .
. . .
. . .









With reference to FIG. 13, to show the infrared image, a grayscale tone is associated to every temperature. The whiter the tone, the higher the temperature, and the darker the tone, the lower the temperature. White is associated with the highest temperature and black is associated with the lowest temperature due the natural physical phenomena that all materials emits light when warmed and, the warmer the temperature, the whiter the light emitted above their own light emitting threshold. A simple demonstration of this principle can be seen in FIG. 27. All other intermediary values have their tones between white and black. To do this, it is necessary for the thermal camera or post processing software operator to choose the upper and lower temperature limits.
This is attained by regulating firmware controls at the camera and this control is usually available in all thermal cameras. Another option is the operator set these values using a proper adjustment command, generally available in any pos-treatment thermal software. In this specific example, it was chosen the top of the thermal image as 30° C. and the bottom value as 15° C. to make the oven and its parts and components visible and identifiable as can be seen in FIG. 14. It is worth noting, for comparison, that if a “wrong” the upper temperature limit is set at 200° C. and the lower temperature limit is set at 0° C., an image shown in FIG. 15 would be obtained, making it very difficult, if not impossible to identify the oven's components.
When suitable upper and lower limits are chosen, every pixel value will have its temperature value proportionally presented between these two limits as can be seen at the side scales in FIGS. 14, 16a, 16b and 17. If the value of a pixel is greater or equal to say 30° in FIG. 14, it will be presented in white. If a value pixel is lower or equal to 15° C., it will be present in black. These two over limits adjustments (up and low) are common to all thermal image cameras and are not exclusive to this invention. All other values between these superior and inferior limits will be presented in a linear and proportional grey tone.
Example 2
Conventional False Color-Added Infrared Image (“Iron” and “Rainbow”)
(Related Art)
Adding false colors to the image obtained in Example 1 (FIG. 13) entails a change of the conversion color RGB table algorithm recorded at the thermal camera firmware, or in the thermal pos-processing software from white-grey-black tones, to color tones. On the exemplary oven to colors, keeping the same top and bottom limits, is shown in FIGS. 16a and 16b. Similar examples of other objects are shown in FIGS. 10 and 11. As can be easily seen, colors applied by conventional methods are tiring to the eye and usually give too much color information to be interpreted and understood. Too much color stresses the operators' eyes and brain causing him or her to commit more errors as the working day advances. Such errors are very expensive for the users of infrared imaging because the spots located are generally linked to severe damages on the equipments or industrial or power instalations inspected with this technology.
Example 3
Step-by-step Procedure for Converting a Thermal Image Using Inverted Black and White Plus Color Mixing Process on FIG. 17
The following steps and considerations are followed to convert a thermal image using an exemplary process according to this invention. :
1. The color gradient that will be used in the color portion of the image must be chosen carefully. The color palette can be any of the millions of color arrangements the human eye can see but those palettes with too many colors will usually produce very confusing thermal images. In FIG. 6 there are several examples of color sequences that are added to inverted black and white tones. It shall be noted that more than 6 different colors plus black and white are usually tiring and confusing to the human eye. Nevertheless, the purpose of the invention is to split the thermal information contained in a thermal image into two parts; a first one related to the important temperatures that are represented in colors, and a second one correlated to inverted black and white tones to mimic the X-ray effect and that shows the context where the interest temperatures are immersed.
2. Every color in any arrangement has an associated RGB (Red, Green, Blue) standardized code for all computer and digital video output devices. In these codes, the red, green or blue intensities vary from 0 to 255. Being so, every color has its own three RGB number values. The color part sequence of the colors applied in FIG. 17 is shown in Table 4. The inverted black and tones or grayscale part is added bellow the color portion of the image and have their own RGB codes shown in Table 5. It shall be noted the last line of the Table 4 is the first line of the Table 5 so the total amount of lines is 256.







TABLE 4







RGB Values of Colors Shown in FIG. 17











LINE
R
G
B
COLOR














1
248
248
248
Almost






White


2
248
248
248


3
247
247
231


4
246
246
214


5
246
245
196


6
245
244
179


7
244
243
162


8
243
241
145


9
242
240
128


10
242
239
110


11
241
238
93


12
240
237
76


13
239
236
59


14
239
228
74


15
239
218
72


16
238
209
70


17
237
199
68


18
237
190
66
Yellow






Gold


19
236
181
64


20
235
171
62


21
235
162
60


22
234
152
58


23
233
143
56


24
233
134
55


25
232
124
53


26
232
115
51


27
231
105
49
Orange


28
230
96
47


29
230
87
45


30
229
77
43


31
228
68
41


32
228
58
39


33
227
49
37


34
220
49
36


35
214
50
36


36
207
50
35


37
201
50
34


38
194
51
34


39
188
51
33
Dark Red


40
181
52
32


41
175
52
32


42
168
52
31


43
161
53
30


44
155
53
30


45
148
53
29


46
142
54
28


47
135
54
27


48
129
54
27


49
122
55
26


50
115
55
25


51
109
55
25


52
102
56
24
Brown


53
96
56
23


54
89
57
23


55
83
57
22


56
76
57
21


57
70
58
21


58
63
58
20


59
60
63
26


60
56
69
32


61
53
74
38


62
50
79
44


63
47
84
49


64
43
90
55


65
40
95
61


66
37
100
67
Dark Green


67
33
106
73


68
30
111
79


69
34
115
86


70
37
120
93


71
41
124
100


72
44
128
107


73
48
133
114


74
52
137
121


75
55
141
128


76
59
146
135


77
62
150
142


78
66
154
150


79
70
159
157


80
73
163
164


81
77
168
171


82
80
172
178
Light Blue


83
84
176
185


84
88
181
192


85
91
185
199


86
95
189
206


87
98
194
213


88
102
198
220


89
99
192
217


90
95
186
214


91
92
180
211


92
88
175
209


93
85
169
206


94
81
163
203


95
78
157
200


96
74
151
197


97
71
145
194


98
67
140
192


99
64
134
189


100
61
128
186


101
57
122
183
Medium






Blue


102
54
116
180


103
50
110
177


104
47
104
174


105
43
99
172


106
40
93
169


107
36
87
166


108
33
81
163


109
32
77
155


110
31
74
148


111
30
70
140


112
28
67
132


113
27
63
125


114
26
60
117


115
25
56
109


116
24
53
102


117
23
49
94
Dark blue


118
22
46
86


119
20
42
79


120
19
38
71


121
18
35
64


122
17
31
56


123
16
28
48


124
15
24
41


125
13
21
33


126
12
17
25


127
11
14
18


128
10
10
10
Black
















TABLE 5







RGB Values of Grayscale Tones Shown in FIG. 17.











LINE
R
G
B
COLOR














1
10
10
10
Black


2
12
12
12


3
13
13
13


4
15
15
15


5
17
17
17


6
18
18
18


7
20
20
20


8
22
22
22


9
23
23
23


10
25
25
25


11
27
27
27


12
28
28
28


13
30
30
30


14
32
32
32


15
34
34
34


16
35
35
35


17
37
37
37


18
39
39
39


19
40
40
40


20
42
42
42


21
44
44
44


22
45
45
45


23
47
47
47


24
49
49
49


25
50
50
50


26
52
52
52


27
54
54
54


28
55
55
55


29
57
57
57


30
59
59
59


31
60
60
60


32
62
62
62


33
64
64
64


34
65
65
65


35
67
67
67


36
69
69
69


37
70
70
70


38
72
72
72


39
74
74
74


40
76
76
76


41
77
77
77


42
79
79
79


43
81
81
81


44
82
82
82


45
84
84
84


46
86
86
86


47
87
87
87


48
89
89
89


49
91
91
91


50
92
92
92


51
94
94
94


52
96
96
96


53
97
97
97


54
99
99
99
Dark Grey


55
101
101
101


56
102
102
102


57
104
104
104


58
106
106
106


59
107
107
107


60
109
109
109


61
111
111
111


62
112
112
112


63
114
114
114


64
116
116
116


65
118
118
118


66
119
119
119


67
121
121
121


68
123
123
123


69
124
124
124


70
126
126
126


71
128
128
128


72
129
129
129


73
131
131
131


74
133
133
133


75
134
134
134


76
136
136
136


77
138
138
138


78
139
139
139


79
141
141
141


80
143
143
143


81
144
144
144


82
146
146
146


83
148
148
148


84
149
149
149


85
151
151
151


86
153
153
153


87
154
154
154


88
156
156
156


89
158
158
158


90
160
160
160


91
161
161
161


92
163
163
163


93
165
165
165


94
166
166
166


95
168
168
168


96
170
170
170


97
171
171
171


98
173
173
173


99
175
175
175


100
176
176
176


101
178
178
178


102
180
180
180


103
181
181
181


104
183
183
183


105
185
185
185


106
186
186
186


107
188
188
188


108
190
190
190


109
191
191
191


110
193
193
193


111
195
195
195


112
196
196
196


113
198
198
198


114
200
200
200


115
202
202
202


116
203
203
203


117
205
205
205


118
207
207
207


119
208
208
208


120
210
210
210


121
212
212
212


122
213
213
213


123
215
215
215


124
217
217
217


125
218
218
218


126
220
220
220


127
220
220
220


128
200
200
200


129
200
200
200
Light Gray









The grayscale tones are generated the same way the colors are, choosing almost black color or near (R=10, G=10, B=10—Line 1 in Table 5) to be the next value to be considered bellow the last color (R=G=B=—Line 127 in Table 4, coming up to down) and the brighter tone, usually a clear gray tone (R=200, G=200, B=200—Line 129 in Table 5) as being the last tone on the image. Having chosen this, the intermediary tones are simply divided by the exceeding number of lines, to sum the total amount of desired tons (100, 120, 256, etc) suitable for the physical characteristics of the camera hardware. The final result is a smooth mixing between inverted black and white and colors producing images like the ones presented at FIG. 17.
As a starting point, it is of importance to always correlate the inverted black and white portion to the lower temperatures and the color tones to the higher temperatures to produce the optimum result. As can be seen in FIG. 6, there are several different proportions on colors versus inverted black and white tones, causing different percent distribution but the general effect is always kept. But all of them follow the same mixing principle.
3. Since the upper and lower temperature limits of the image are set, the total number of colors (in this example 256) is proportionally distributed between the two extreme values.
4. The result of this division will then be electronically and proportionally and sequentially correlated to every one of the value pixels forming the final image. The pixels that have values higher that the upper temperature limit will be correlated to the first (top) line of the final color codes table. The pixels that have values lower that the lower temperature limit will be correlated to the last (bottom) line of the final color codes table. The intermediary values will be correlated correspondently to the intermediary values of the table.
Using the oven thermal image as an example, the temperature values of which are shown in Table 3, the first pixel (column 1, line 1) will have a value of 21.4° C. Because the chosen span between the upper temperature limit (30° C.) and the lower temperature limit (15° C.) is 15° C., the total span of 15° will be divided by the total of 256 colors available in this color arrangement. This will result in 0.0586 degrees per tone (15° C./256 tones=0.058594° C. per tone). Since 21.4° C. is near the lower limit of 15° than from the up limit, let's start from the bottom temperature of 15° C. in order to obtain the value of 21.4° C. The difference is then 6.4° C. or 109 tone lines from bottom to top (6.4° C./0.058594° C./tone=109.22 tones). Counting the 109 lines from bottom to top in Table 6, the correspondent color will be the RGB code of “103 103 103”. This means that the pixel will have the color of FIG. 18 and this can be seen at the left top corner of the FIG. 19 since the very first pixel at the column 1 and line 1 of this thermal image has this very color.







TABLE 6







RGB Values of Colors and Grayscale Tones Shown in FIG. 17













LINE




LINE



UP
R
G
B
COLOR
DOWN
TEMP
















1
248
248
248
Almost
256
30.0° C.






White


2
248
248
248

255
29.9° C.


3
246
246
214

254
29.9° C.


4
245
244
179

253
29.8° C.


5
243
241
145

252
29.8° C.


6
242
239
110

251
29.7° C.


7
240
237
76
Yellow
250
29.6° C.


8
238
235
42

249
29.6° C.


9
239
218
72

248
29.5° C.


10
237
199
68

247
29.5° C.


11
236
181
64

246
29.4° C.


12
235
162
60

245
29.4° C.


13
233
143
56

244
29.3° C.


14
232
124
53

243
29.2° C.


15
231
105
49

242
29.2° C.


16
230
87
45

241
29.1° C.


17
228
68
41

240
29.1° C.


18
227
49
37
Almost Red
239
29.0° C.


19
214
50
36

238
28.9° C.


20
201
50
34

237
28.9° C.


21
188
51
33

236
28.8° C.


22
175
52
32

235
28.8° C.


23
161
53
30

234
28.7° C.


24
148
53
29

233
28.7° C.


25
135
54
27

232
28.6° C.


26
122
55
26

231
28.5° C.


27
109
55
25
Orange
230
28.5° C.


28
96
56
23

229
28.4° C.


29
83
57
22

228
28.4° C.


30
70
58
21

227
28.3° C.


31
56
69
32

226
28.2° C.


32
50
79
44

225
28.2° C.


33
43
90
55

224
28.1° C.


34
37
100
67

223
28.1° C.


35
30
111
79

222
28.0° C.


36
37
120
93

221
27.9° C.


37
44
128
107

220
27.9° C.


38
52
137
121

219
27.8° C.


39
59
146
135

218
27.8° C.


40
66
154
149

217
27.7° C.


41
73
163
164

216
27.7° C.


42
80
172
178

215
27.6° C.


43
88
181
192

214
27.5° C.


44
95
189
206

213
27.5° C.


45
102
198
220

212
27.4° C.


46
95
186
214

211
27.4° C.


47
88
175
209

210
27.3° C.


48
81
163
203

209
27.2° C.


49
74
151
197

208
27.2° C.


50
67
140
192

207
27.1° C.


51
61
128
186

206
27.1° C.


52
54
116
180

205
27.0° C.


53
47
104
174

204
27.0° C.


54
40
93
169

203
26.9° C.


55
33
81
163

202
26.8° C.


56
31
74
148

201
26.8° C.


57
28
67
132

200
26.7° C.


58
26
60
117

199
26.7° C.


59
24
53
102

198
26.6° C.


60
21
46
86

197
26.5° C.


61
19
38
71

196
26.5° C.


62
17
31
56

195
26.4° C.


63
15
24
41

194
26.4° C.


64
12
17
25

193
26.3° C.


65
10
10
10

192
26.3° C.


66
11
11
11

191
26.2° C.


67
12
12
12

190
26.1° C.


68
13
13
13

189
26.1° C.


69
14
14
14

188
26.0° C.


70
16
16
16

187
26.0° C.


71
17
17
17

186
25.9° C.


72
18
18
18

185
25.8° C.


73
19
19
19

184
25.8° C.


74
20
20
20

183
25.7° C.


75
21
21
21

182
25.7° C.


76
22
22
22

181
25.6° C.


77
23
23
23

180
25.5° C.


78
25
25
25

179
25.5° C.


79
26
26
26

178
25.4° C.


80
27
27
27

177
25.4° C.


81
28
28
28

176
25.3° C.


82
29
29
29
Light Blue
175
25.3° C.


83
30
30
30

174
25.2° C.


84
31
31
31

173
25.1° C.


85
32
32
32

172
25.1° C.


86
34
34
34

171
25.0° C.


87
35
35
35

170
25.0° C.


88
36
36
36

169
24.9° C.


89
37
37
37

168
24.8° C.


90
38
38
38

167
24.8° C.


91
39
39
39

166
24.7° C.


92
40
40
40

165
24.7° C.


93
41
41
41

164
24.6° C.


94
42
42
42

163
24.6° C.


95
44
44
44

162
24.5° C.


96
45
45
45

161
24.4° C.


97
46
46
46

160
24.4° C.


98
47
47
47

159
24.3° C.


99
48
48
48

158
24.3° C.


100
49
49
49

157
24.2° C.


101
50
50
50

156
24.1° C.


102
51
51
51

155
24.1° C.


103
53
53
53

154
24.0° C.


104
54
54
54

153
24.0° C.


105
55
55
55

152
23.9° C.


106
56
56
56

151
23.8° C.


107
57
57
57

150
23.8° C.


108
58
58
58

149
23.7° C.


109
59
59
59

148
23.7° C.


110
60
60
60

147
23.6° C.


111
62
62
62

146
23.6° C.


112
63
63
63

145
23.5° C.


113
64
64
64

144
23.4° C.


114
65
65
65

143
23.4° C.


115
66
66
66

142
23.3° C.


116
67
67
67

141
23.3° C.


117
68
68
68

140
23.2° C.


118
69
69
69

139
23.1° C.


119
70
70
70

138
23.1° C.


120
72
72
72

137
23.0° C.


121
73
73
73

136
23.0° C.


122
74
74
74

135
22.9° C.


123
75
75
75

134
22.9° C.


124
76
76
76

133
22.8° C.


125
77
77
77

132
22.7° C.


126
78
78
78

131
22.7° C.


127
79
79
79

130
22.6° C.


128
81
81
81

129
22.6° C.


129
82
82
82

128
22.5° C.


130
83
83
83

127
22.4° C.


131
84
84
84

126
22.4° C.


132
85
85
85

125
22.3° C.


133
86
86
86

124
22.3° C.


134
87
87
87

123
22.2° C.


135
88
88
88

122
22.1° C.


136
90
90
90

121
22.1° C.


137
91
91
91

120
22.0° C.


138
92
92
92

119
22.0° C.


139
93
93
93

118
21.9° C.


140
94
94
94

117
21.9° C.


141
95
95
95

116
21.8° C.


142
96
96
96

115
21.7° C.


143
97
97
97

114
21.7° C.


144
98
98
98

113
21.6° C.


145
100
100
100

112
21.6° C.


146
101
101
101

111
21.5° C.


147
102
102
102

110
21.4° C.


148
103
103
103

109
21.4° C.


149
104
104
104

108
21.3° C.


150
105
105
105

107
21.3° C.


151
106
106
106

106
21.2° C.


152
107
107
107

105
21.2° C.


153
109
109
109

104
21.1° C.


154
110
110
110

103
21.0° C.


155
111
111
111

102
21.0° C.


156
112
112
112

101
20.9° C.


157
113
113
113

100
20.9° C.


158
114
114
114

99
20.8° C.


159
115
115
115

98
20.7° C.


160
116
116
116

97
20.7° C.


161
118
118
118

96
20.6° C.


162
119
119
119

95
20.6° C.


163
120
120
120

94
20.5° C.


164
121
121
121

93
20.4° C.


165
122
122
122

92
20.4° C.


166
123
123
123

91
20.3° C.


167
124
124
124

90
20.3° C.


168
125
125
125

89
20.2° C.


169
126
126
126

88
20.2° C.


170
128
128
128

87
20.1° C.


171
129
129
129

86
20.0° C.


172
130
130
130

85
20.0° C.


173
131
131
131

84
19.9° C.


174
132
132
132

83
19.9° C.


175
133
133
133

82
19.8° C.


176
134
134
134

81
19.7° C.


177
135
135
135

80
19.7° C.


178
137
137
137

79
19.6° C.


179
138
138
138

78
19.6° C.


180
139
139
139

77
19.5° C.


181
140
140
140

76
19.5° C.


182
141
141
141

75
19.4° C.


183
142
142
142

74
19.3° C.


184
143
143
143

73
19.3° C.


185
144
144
144

72
19.2° C.


186
146
146
146

71
19.2° C.


187
147
147
147

70
19.1° C.


188
148
148
148

69
19.0° C.


189
149
149
149

68
19.0° C.


190
150
150
150

67
18.9° C.


191
151
151
151

66
18.9° C.


192
152
152
152

65
18.8° C.


193
153
153
153

64
18.8° C.


194
154
154
154

63
18.7° C.


195
156
156
156

62
18.6° C.


196
157
157
157

61
18.6° C.


197
158
158
158

60
18.5° C.


198
159
159
159

59
18.5° C.


199
160
160
160

58
18.4° C.


200
161
161
161

57
18.3° C.


201
162
162
162

56
18.3° C.


202
163
163
163

55
18.2° C.


203
165
165
165

54
18.2° C.


204
166
166
166

53
18.1° C.


205
167
167
167

52
18.0° C.


206
168
168
168

51
18.0° C.


207
169
169
169

50
17.9° C.


208
170
170
170

49
17.9° C.


209
171
171
171

48
17.8° C.


210
172
172
172

47
17.8° C.


211
174
174
174

46
17.7° C.


212
175
175
175

45
17.6° C.


213
176
176
176

44
17.6° C.


214
177
177
177

43
17.5° C.


215
178
178
178

42
17.5° C.


216
179
179
179

41
17.4° C.


217
180
180
180

40
17.3° C.


218
181
181
181

39
17.3° C.


219
182
182
182

38
17.2° C.


220
184
184
184

37
17.2° C.


221
185
185
185

36
17.1° C.


222
186
186
186

35
17.1° C.


223
187
187
187

34
17.0° C.


224
188
188
188

33
16.9° C.


225
189
189
189

32
16.9° C.


226
190
190
190

31
16.8° C.


227
191
191
191

30
16.8° C.


228
193
193
193

29
16.7° C.


229
194
194
194

28
16.6° C.


230
195
195
195

27
16.6° C.


231
196
196
196

26
16.5° C.


232
197
197
197

25
16.5° C.


233
198
198
198

24
16.4° C.


234
199
199
199

23
16.3° C.


235
200
200
200

22
16.3° C.


236
202
202
202

21
16.2° C.


237
203
203
203

20
16.2° C.


238
204
204
204

19
16.1° C.


239
205
205
205

18
16.1° C.


240
206
206
206

17
16.0° C.


241
207
207
207

16
15.9° C.


242
208
208
208

15
15.9° C.


243
209
209
209

14
15.8° C.


244
210
210
210

13
15.8° C.


245
212
212
212

12
15.7° C.


246
213
213
213

11
15.6° C.


247
214
214
214

10
15.6° C.


248
215
215
215

9
15.5° C.


249
216
216
216

8
15.5° C.


250
217
217
217

7
15.4° C.


251
218
218
218

6
15.4° C.


252
219
219
219

5
15.3° C.


253
221
221
221

4
15.2° C.


254
221
221
221

3
15.2° C.


255
221
221
221

2
15.1° C.


256
221
221
221
Light Gray
1
15.1° C.









Another example can be seen in the middle of FIG. 19. Taking for instance the hot spot marked in this figure, it reads 27.5° C. The pixel number of this hot spot is X=140 and Y=113.
Referring to the part of the complete Table 8 that has this line and column, we find the same value that is marked in the FIG. 19. As written above, every tone line corresponds to 0.0586 degrees per tone and from 15° to 27.5° C. there are 12.5 ° C. Dividing this 12.5 by 0.0586 we get 213 lines. Counting the lines from the bottom temperature in Table 6, we get the 95 189 206 RGB code, which is the color presented at the FIG. 20. This is the same color presented at the exact hot spot localization, as we can see in the FIG. 19 and in the zoomed image at FIG. 21.
Example 4
Step-by-step Procedure for Converting a Thermal Image Using Inverted Black and White Plus Color Mixing Process on FIG. 22
In this example, the same method is applied to another thermal image. This example uses the same “High Tension Terminal” thermal image shown in the lower left-hand corner in FIG. 9 that can be seen with its temperatures side scale in FIG. 22. The inverted black and white with color scheme applied to this image is the same one applied to FIG. 17 and presented with its RGB codes in Table 7.







TABLE 7







RGB Values of Colors and Grayscale Tones Shown in FIG. 22













LINE




LINE



UP
R
G
B
COLOR
DOWN
TEMP
















1
248
248
248
Almost
256
89.0° C.






White


2
248
248
248

255
88.7° C.


3
246
246
214

254
88.4° C.


4
245
244
179

253
88.1° C.


5
243
241
145

252
87.8° C.


6
242
239
110

251
87.4° C.


7
240
237
76
Yellow
250
87.1° C.


8
238
235
42

249
86.8° C.


9
239
218
72

248
86.5° C.


10
237
199
68

247
86.2° C.


11
236
181
64

246
85.9° C.


12
235
162
60

245
85.6° C.


13
233
143
56

244
85.3° C.


14
232
124
53

243
84.9° C.


15
231
105
49

242
84.6° C.


16
230
87
45

241
84.3° C.


17
228
68
41

240
84.0° C.


18
227
49
37
Almost Red
239
83.7° C.


19
214
50
36

238
83.4° C.


20
201
50
34

237
83.1° C.


21
188
51
33

236
82.8° C.


22
175
52
32

235
82.4° C.


23
161
53
30

234
82.1° C.


24
148
53
29

233
81.8° C.


25
135
54
27

232
81.5° C.


26
122
55
26

231
81.2° C.


27
109
55
25
Orange
230
80.9° C.


28
96
56
23

229
80.6° C.


29
83
57
22

228
80.3° C.


30
70
58
21

227
79.9° C.


31
56
69
32

226
79.6° C.


32
50
79
44

225
79.3° C.


33
43
90
55

224
79.0° C.


34
37
100
67

223
78.7° C.


35
30
111
79

222
78.4° C.


36
37
120
93

221
78.1° C.


37
44
128
107

220
77.8° C.


38
52
137
121

219
77.4° C.


39
59
146
135

218
77.1° C.


40
66
154
149

217
76.8° C.


41
73
163
164

216
76.5° C.


42
80
172
178

215
76.2° C.


43
88
181
192

214
75.9° C.


44
95
189
206

213
75.6° C.


45
102
198
220

212
75.3° C.


46
95
186
214

211
74.9° C.


47
88
175
209

210
74.6° C.


48
81
163
203

209
74.3° C.


49
74
151
197

208
74.0° C.


50
67
140
192

207
73.7° C.


51
61
128
186

206
73.4° C.


52
54
116
180

205
73.1° C.


53
47
104
174

204
72.8° C.


54
40
93
169

203
72.4° C.


55
33
81
163

202
72.1° C.


56
31
74
148

201
71.8° C.


57
28
67
132

200
71.5° C.


58
26
60
117

199
71.2° C.


59
24
53
102

198
70.9° C.


60
21
46
86

197
70.6° C.


61
19
38
71

196
70.3° C.


62
17
31
56

195
69.9° C.


63
15
24
41

194
69.6° C.


64
12
17
25

193
69.3° C.


65
10
10
10

192
69.0° C.


66
11
11
11

191
68.7° C.


67
12
12
12

190
68.4° C.


68
13
13
13

189
68.1° C.


69
14
14
14

188
67.8° C.


70
16
16
16

187
67.4° C.


71
17
17
17

186
67.1° C.


72
18
18
18

185
66.8° C.


73
19
19
19

184
66.5° C.


74
20
20
20

183
66.2° C.


75
21
21
21

182
65.9° C.


76
22
22
22

181
65.6° C.


77
23
23
23

180
65.3° C.


78
25
25
25

179
64.9° C.


79
26
26
26

178
64.6° C.


80
27
27
27

177
64.3° C.


81
28
28
28

176
64.0° C.


82
29
29
29
Light Blue
175
63.7° C.


83
30
30
30

174
63.4° C.


84
31
31
31

173
63.1° C.


85
32
32
32

172
62.8° C.


86
34
34
34

171
62.4° C.


87
35
35
35

170
62.1° C.


88
36
36
36

169
61.8° C.


89
37
37
37

168
61.5° C.


90
38
38
38

167
61.2° C.


91
39
39
39

166
60.9° C.


92
40
40
40

165
60.6° C.


93
41
41
41

164
60.3° C.


94
42
42
42

163
59.9° C.


95
44
44
44

162
59.6° C.


96
45
45
45

161
59.3° C.


97
46
46
46

160
59.0° C.


98
47
47
47

159
58.7° C.


99
48
48
48

158
58.4° C.


100
49
49
49

157
58.1° C.


101
50
50
50

156
57.8° C.


102
51
51
51

155
57.4° C.


103
53
53
53

154
57.1° C.


104
54
54
54

153
56.8° C.


105
55
55
55

152
56.5° C.


106
56
56
56

151
56.2° C.


107
57
57
57

150
55.9° C.


108
58
58
58

149
55.6° C.


109
59
59
59

148
55.3° C.


110
60
60
60

147
54.9° C.


111
62
62
62

146
54.6° C.


112
63
63
63

145
54.3° C.


113
64
64
64

144
54.0° C.


114
65
65
65

143
53.7° C.


115
66
66
66

142
53.4° C.


116
67
67
67

141
53.1° C.


117
68
68
68

140
52.8° C.


118
69
69
69

139
52.4° C.


119
70
70
70

138
52.1° C.


120
72
72
72

137
51.8° C.


121
73
73
73

136
51.5° C.


122
74
74
74

135
51.2° C.


123
75
75
75

134
50.9° C.


124
76
76
76

133
50.6° C.


125
77
77
77

132
50.3° C.


126
78
78
78

131
49.9° C.


127
79
79
79

130
49.6° C.


128
81
81
81

129
49.3° C.


129
82
82
82

128
49.0° C.


130
83
83
83

127
48.7° C.


131
84
84
84

126
48.4° C.


132
85
85
85

125
48.1° C.


133
86
86
86

124
47.8° C.


134
87
87
87

123
47.4° C.


135
88
88
88

122
47.1° C.


136
90
90
90

121
46.8° C.


137
91
91
91

120
46.5° C.


138
92
92
92

119
46.2° C.


139
93
93
93

118
45.9° C.


140
94
94
94

117
45.6° C.


141
95
95
95

116
45.3° C.


142
96
96
96

115
44.9° C.


143
97
97
97

114
44.6° C.


144
98
98
98

113
44.3° C.


145
100
100
100

112
44.0° C.


146
101
101
101

111
43.7° C.


147
102
102
102

110
43.4° C.


148
103
103
103

109
43.1° C.


149
104
104
104

108
42.8° C.


150
105
105
105

107
42.4° C.


151
106
106
106

106
42.1° C.


152
107
107
107

105
41.8° C.


153
109
109
109

104
41.5° C.


154
110
110
110

103
41.2° C.


155
111
111
111

102
40.9° C.


156
112
112
112

101
40.6° C.


157
113
113
113

100
40.3° C.


158
114
114
114

99
39.9° C.


159
115
115
115

98
39.6° C.


160
116
116
116

97
39.3° C.


161
118
118
118

96
39.0° C.


162
119
119
119

95
38.7° C.


163
120
120
120

94
38.4° C.


164
121
121
121

93
38.1° C.


165
122
122
122

92
37.8° C.


166
123
123
123

91
37.4° C.


167
124
124
124

90
37.1° C.


168
125
125
125

89
36.8° C.


169
126
126
126

88
36.5° C.


170
128
128
128

87
36.2° C.


171
129
129
129

86
35.9° C.


172
130
130
130

85
35.6° C.


173
131
131
131

84
35.3° C.


174
132
132
132

83
34.9° C.


175
133
133
133

82
34.6° C.


176
134
134
134

81
34.3° C.


177
135
135
135

80
34.0° C.


178
137
137
137

79
33.7° C.


179
138
138
138

78
33.4° C.


180
139
139
139

77
33.1° C.


181
140
140
140

76
32.8° C.


182
141
141
141

75
32.4° C.


183
142
142
142

74
32.1° C.


184
143
143
143

73
31.8° C.


185
144
144
144

72
31.5° C.


186
146
146
146

71
31.2° C.


187
147
147
147

70
30.9° C.


188
148
148
148

69
30.6° C.


189
149
149
149

68
30.3° C.


190
150
150
150

67
29.9° C.


191
151
151
151

66
29.6° C.


192
152
152
152

65
29.3° C.


193
153
153
153

64
29.0° C.


194
154
154
154

63
28.7° C.


195
156
156
156

62
28.4° C.


196
157
157
157

61
28.1° C.


197
158
158
158

60
27.8° C.


198
159
159
159

59
27.4° C.


199
160
160
160

58
27.1° C.


200
161
161
161

57
26.8° C.


201
162
162
162

56
26.5° C.


202
163
163
163

55
26.2° C.


203
165
165
165

54
25.9° C.


204
166
166
166

53
25.6° C.


205
167
167
167

52
25.3° C.


206
168
168
168

51
24.9° C.


207
169
169
169

50
24.6° C.


208
170
170
170

49
24.3° C.


209
171
171
171

48
24.0° C.


210
172
172
172

47
23.7° C.


211
174
174
174

46
23.4° C.


212
175
175
175

45
23.1° C.


213
176
176
176

44
22.8° C.


214
177
177
177

43
22.4° C.


215
178
178
178

42
22.1° C.


216
179
179
179

41
21.8° C.


217
180
180
180

40
21.5° C.


218
181
181
181

39
21.2° C.


219
182
182
182

38
20.9° C.


220
184
184
184

37
20.6° C.


221
185
185
185

36
20.3° C.


222
186
186
186

35
19.9° C.


223
187
187
187

34
19.6° C.


224
188
188
188

33
19.3° C.


225
189
189
189

32
19.0° C.


226
190
190
190

31
18.7° C.


227
191
191
191

30
18.4° C.


228
193
193
193

29
18.1° C.


229
194
194
194

28
17.8° C.


230
195
195
195

27
17.4° C.


231
196
196
196

26
17.1° C.


232
197
197
197

25
16.8° C.


233
198
198
198

24
16.5° C.


234
199
199
199

23
16.2° C.


235
200
200
200

22
15.9° C.


236
202
202
202

21
15.6° C.


237
203
203
203

20
15.3° C.


238
204
204
204

19
14.9° C.


239
205
205
205

18
14.6° C.


240
206
206
206

17
14.3° C.


241
207
207
207

16
14.0° C.


242
208
208
208

15
13.7° C.


243
209
209
209

14
13.4° C.


244
210
210
210

13
13.1° C.


245
212
212
212

12
12.8° C.


246
213
213
213

11
12.4° C.


247
214
214
214

10
12.1° C.


248
215
215
215

9
11.8° C.


249
216
216
216

8
11.5° C.


250
217
217
217

7
11.2° C.


251
218
218
218

6
10.9° C.


252
219
219
219

5
10.6° C.


253
221
221
221

4
10.3° C.


254
221
221
221

3
 9.9° C.


255
221
221
221

2
 9.6° C.


256
221
221
221
Light Gray
1
 9.3° C.









A hot spot in this figure is chosen that represents an important temperature in the electrical terminal, now presented as FIG. 23a. The precise pixel position of this hot spot is line 93 and column 112 and its temperature value is 83.6° C. as can be seen at the zoomed FIG. 23b and in Table 9. The good quality chosen temperature span to this thermal image was 80° C., beginning at 9° C. as the lowest temperature, and finishing as 89° C. as the highest temperature. Using the same calculation as above in Example 2, we have 256 tones to cover 80° C. Dividing 80 by 256 we have 0.3125 ° C. for every tone. Subtracting the minimum image temperature of 9° C. from the hot spot temperature of 83.6° C. we arrive at 74.6° C. Dividing again the 74.6° C. by the 0.3125 degrees per tone, we obtain 239 lines above the lowest limit temperature that is 9° C. From Table 6, we find that counting from the last line to the top 239 lines we get the line 18 that has the following RGB code: 227 49 37 and has a color presented in FIG. 24. Note that 239 plus 18 is equal to 257 and the difference of 1 line is due to decimals roundings made for this demonstration purposes. Zooming on FIG. 23, we can see that this is exactly the same temperature shown inside the selected hotspot of FIG. 25.
The same calculation is performed using the superior temperature limit. The chosen highest temperature is 89° C. The hotspot temperature is 83.6° C. Accordingly, there is a difference from the hotspot to the top temperature of 5.4° C. Since there are 0.3125 degrees per tone, 5.4° C. need to be divided by the 0.3125° C. per tone to have a total rounded up to 17 lines from top to bottom, beginning at the highest temperature. In Table 7 we find that the RGB color of line 17 has the RGB code of 228 68 41. This line is just 1 (one) line above the line calculated using the lower temperature limit due to rounding the decimals successively during calculations. Visually, the color is almost indistinguishable from line 18 as can be seen at FIG. 26 since the RGB codes are nearly identical.
Then when the inverted black and white colors are added, between the same upper and lower limits, the resultant thermal image becomes clearer, not tiring to view and easy understandable as can be seen in FIGS. 19, 22 and the remaining images in FIG. 12.
All mathematical operations are done by general electronic circuitry that is different from one thermal camera manufacturer to another. Despite of this, the visual video output that follows this color plus inverted black and white tones will always present a much better image discrimination and a high contrast definition which makes a large difference to the human eye and mind that has to view, understand and interpret thermal images for prolonged periods of time.
This invention is not to be limited to the specific embodiments disclosed herein and modifications for various applications and other embodiments are intended to be included within the scope of the appended claims. While this invention has been described in connection with particular examples thereof, the true scope of the invention should not be so limited since other modifications will become apparent to the skilled practitioner upon a study of the drawings, specification, and following claims.
All publications and patent applications mentioned in this specification are indicative of the level of skill of those skilled in the art to which this invention pertains. All publications and patent applications mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication or patent application mentioned in this specification was specifically and individually indicated to be incorporated by reference.

## Claims

1. A method for enhancing visualization of infrared images of imaged objects, the method comprising: dividing temperature data obtained from an infrared camera at least into a first set of temperature data and a second set of temperature data, wherein the first set of temperature data comprises temperatures selected to be visualized with color, and the second set of temperature data comprises temperatures not to be visualized with color but instead visualized in inverted black and white; converting the temperatures selected to be visualized with color into color tones; converting the temperatures not to be visualized with color into black and white tones; and mixing the color tones and the black and white tones into a single image; wherein:
said dividing temperature data obtained from an infrared camera at least into a first set of temperature data and a second set of temperature data comprises setting an upper temperature value and a lower temperature value for the first set of temperature data, assigning temperatures falling within the interval between the upper temperature value and the lower temperature value, inclusive of said values, to said first set of temperature data and assigning temperatures falling outside the interval between the upper temperature value and the lower temperature value to said second set of temperature data
said converting the temperatures selected to be visualized with color into color tones comprises selecting a color palette and evenly distributing and associating RGB values of colors in said color palette to said temperatures selected to be visualized with color;
said converting the temperatures not to be visualized with color into black and white tones comprises selecting a black and white palette and evenly distributing and associating RGB values of tones in said black and white palette to said temperatures not to be visualized with color;
colors in said color palette are arbitrarily chosen and arranged based on artistic taste;
tones in said black and white palette are arbitrarily chosen and arranged based on artistic taste;

said color palette and said black and white palette are selected from those shown in FIG. 6.

2. A method for enhancing visualization of infrared images of imaged objects, the method comprising: dividing temperature data obtained from an infrared camera at least into a first set of temperature data and a second set of temperature data, wherein the first set of temperature data comprises temperatures selected to be visualized with color, and the second set of temperature data comprises temperatures not to be visualized with color but instead visualized in inverted black and white; converting the temperatures selected to be visualized with color into color tones; converting the temperatures not to be visualized with color into black and white tones; and mixing the color tones and the black and white tones into a single image; wherein:
said dividing temperature data obtained from an infrared camera at least into a first set of temperature data and a second set of temperature data comprises setting an upper temperature value and a lower temperature value for the first set of temperature data, assigning temperatures falling within the interval between the upper temperature value and the lower temperature value, inclusive of said values, to said first set of temperature data and assigning temperatures falling outside the interval between the upper temperature value and the lower temperature value to said second set of temperature data
said converting the temperatures selected to be visualized with color into color tones comprises selecting a color palette and evenly distributing and associating RGB values of colors in said color palette to said temperatures selected to be visualized with color;
said converting the temperatures not to be visualized with color into black and white tones comprises selecting a black and white palette and evenly distributing and associating RGB values of tones in said black and white palette to said temperatures not to be visualized with color;
colors in said color palette are arbitrarily chosen and arranged based on artistic taste;
tones in said black and white palette are arbitrarily chosen and arranged based on artistic taste;
said color palette and said black and white palette are selected from those shown in Table 4.

3. A method for enhancing visualization of infrared images of imaged objects, the method comprising: dividing temperature data obtained from an infrared camera at least into a first set of temperature data and a second set of temperature data, wherein the first set of temperature data comprises temperatures selected to be visualized with color, and the second set of temperature data comprises temperatures not to be visualized with color but instead visualized in inverted black and white; converting the temperatures selected to be visualized with color into color tones; converting the temperatures not to be visualized with color into black and white tones; and mixing the color tones and the black and white tones into a single image; wherein:
said dividing temperature data obtained from an infrared camera at least into a first set of temperature data and a second set of temperature data comprises setting an upper temperature value and a lower temperature value for the first set of temperature data, assigning temperatures falling within the interval between the upper temperature value and the lower temperature value, inclusive of said values, to said first set of temperature data; and assigning temperatures falling outside the interval between the upper temperature value and the lower temperature value to said second set of temperature data;
said converting the temperatures selected to be visualized with color into color tones comprises selecting a color palette and evenly distributing and associating RGB values of colors in said color palette to said temperatures selected to be visualized with color;
said converting the temperatures not to be visualized with color into black and white tones comprises selecting a black and white palette and evenly distributing and associating RGB values of tones in said black and white palette to said temperatures not to be visualized with color;
said color palette and said black and white palette are selected from those shown in FIG. 6.