# Color CCD High-Temperature Measurement Method Based on Matrix Searching
## 2 Method
### Temperature Measurement Realization
 \tag{11}\]  
I\({}_{\text{mn}}\) and j\({}_{\text{mn}}\) are the search addresses of the temperature mapping matrix of the pixels in the m-th row and the n-th column, respectively. According to the obtained search address of each pixel, the corresponding matrix element in the temperature mapping matrix established in the preparation stage is called, and the value is the temperature calculation result  
Figure 2: Schematic diagram of temperature field acquisition image analysis. of the corresponding point of the pixel. Finally, the one-to-one temperature calculation result corresponding to the pixel can be obtained, and the result is output in the form of data. The output form of the CCD temperature measurement method based on matrix search can be divided into data type and image type. Data temperature results are mainly applied to the temperature measurement of a specific position or the temperature measurement of a small temperature field (such as the temperature field caused by a laser). This result can be obtained directly by reading the data of the corresponding pixel position. The image type result is the output spatial temperature mapping image, which can intuitively obtain the temperature distribution of the whole image or the region of interest. The output of the image type result requires post-processing of the temperature data, which is called the temperature visualization process. The block diagram of the temperature visualization program based on the matrix-seeking temperature measurement method is shown in Figure 3.  
After obtaining the heat source image, firstly, the temperature mapping matrix T\({}_{\text{map}}\) and the minimum normalized signals R\({}_{\text{min}}\) and G\({}_{\text{min}}\) were generated in the preparation stage for this measurement into the program. Then the collected heat source image is analyzed to obtain a three-channel image matrix ImageR, ImageG, and ImageB. After the three-channel gray matrix is processed and the normalized R and G values of the image are obtained. Through two nested loop programs, the temperature solution results are assigned to a matrix M\({}_{\text{map}}\) which is the same as the dimension of the image frame through two nested loop programs. The loop variables m and n represent the number of rows and columns, respectively, and \(r_{min}\), \(r_{max}\), \(c_{min}\), and \(c_{max}\) represent the minimum number of rows, the maximum number of rows, the minimum number of columns, and the maximum number of columns, respectively. When calculating pixels in a specific area, \(r_{min}\) is the starting pixel line of the area, \(r_{max}\) is the ending pixel line of the area, and the corresponding column values are the same. For full image calculation, the \(r_{min}\) value is 1, \(r_{max}\) is the total number of rows, and the corresponding column values are the same. After the cycle, the matrix variable M\({}_{\text{map}}\) corresponding to each pixel composed of temperature data will be obtained. Finally, the M\({}_{\text{map}}\) will be converted into grayscale data, and different pseudo-color mapping methods will be selected to obtain the temperature data visualization result. The temperature visualization process can be well-combined with the relatively complete image processing technology. Using comprehensive image blurring, noise reduction, filtering, etc., the details of the corresponding temperature field distribution and change can be well obtained. In addition, by combining the image edge recognition algorithm,  
Figure 3: Block diagram of the temperature visualization program. the temperature mapping region can be quickly determined, thus reducing the calculation amount of the image visualization process and effectively saving the calculation resources. It is worth noting that this method is more inclusive in theory because it transforms the inverse problem-solving process into the forward matrix accurate searching process.