Bull. Hiroshima Inst. Tech. Research Vol. 55（2021）63-76

ArticleSteganographic Image Compression Method with Adaptive Enhancement Code
Embedding and Its Performance Evaluation on 4K Standard Test Images
Isao FURUKAWA ＊ and Junji SUZUKI ＊＊（Received Oct. 31, 2020）

Abstract
We have studied a steganographic image compression algorithm that embeds special codes(i.e., enhancement codes) in the encoder, and extracts these codes in the decoder to reconstructfull-resolution image. The compressed codestream from the encoder also can be decoded bystandard JPEG decoder even though the resolution of reconstructed image decreases by half, sothat this encoder has backward compatibility with JPEG. In embedding enhancement codes into
lower DCT coefficients, there is an upper limit for the amount of codes (i.e., payload) in order tomake the distortion by bit-embedding as small as possible. Although the conventional algorithm
employs the constant number of scans of higher DCT coefficients to create the enhancement
codes, it appears to be a bottleneck for DCT blocks that allow enough room in the payload. We
propose an adaptive determination method of the enhancement codes based on the payloadof each DCT block while conforming to the specifications of JPEG. This method effectively
utilizes the payload in all the DCT blocks, so the quality improvement of the reconstructed
image is expected. Moreover, we propose an HVS-based order rather than zigzag scan order for
embedding the enhancement codes in hope of alleviating the distortion due to bit-replacement.
As a result of evaluation with four 4K standard test images, the adaptive method can increase
the amount of enhancement codes, and this leads to SNR improvement in comparison to theconventional constant method. Some decoded examples of both 4K/2K images are also shown.
Key Words: steganography, image enhancement, JPEG, entropy coding, HVS, 4K image

1. INTRODUCTION

the image resolution obtained from a compressed

Broadcasting services with higher resolution (i.e.,

display device environments. For example, JPEG

4K/8K) than HDTV (high definition television)

2000 for still images and scalable extension ofhave started in recent years [1], and images of

H.264/HEVC (SHVC) for moving images [2] cansuper high definition, wide color gamut, and highrealize the spatial resolution scalability.

codestream is scalable according to network anddynamic range are becoming at hand. On the otherIn such circumstances where various resolution

hand, images on the Internet have a variety ofimages exist in the same realm, we have proposed

resolutions depending on physical constraints such

new image compression scheme with a premise

as network speeds or image size of display devices.

that high-resolution images are more valuable

Therefore, it is desirable for 4K/8K images that

assets than low-resolution ones [3], [4]. The＊＊＊

Department of Computer Science, Faculty of Applied Information Science, Hiroshima Institute of Technology
School of Information Science and Technology, Aichi Prefectural University (retired)― 63 ―

Isao FURUKAWA and Junji SUZUKI

proposed method offers a mechanism to embedof reconstructed high-resolution images improves,secret codes into lower DCT coefficients, andand also that the additional side information needs

only special parties knowing the fact can recover

not to be transmitted from encoder to decoder.

full-resolution images, while others decode low-

The proposed adaptive steganographic encoder

resolution images by using standard JPEG decoder.

controls the amount of run-length Huffman

We call the scheme image enhancement method

codes created from higher DCT coefficients inwith steganographic data embedding (shortly,

such a way that the total length of enhancement

steganographic coding or steganographic encoder/codes becomes smaller than the payload while

decoder). This steganographic encoder uses JPEG

conforming to JPEG specification. In Section 2,

as a basic coding configuration, and embeds run-

we outline the basic system configurations tolength Huffman codes created from 16×16 higher

realize the steganographic encoder and decoder

DCT coefficients into 8×8 lower DCT coefficients.

described above. Adaptive method to terminate

These codes for augmenting visual resolution

the enhancement codes is described in Section 3.

are called enhancement codes, and the output

For embedding the enhancement codes into LSBs

codestream including the secret codes conforms(least significant bits) of lower DCT coefficients,

to JPEG specifications, so that the steganographic

embedding order that is expected to reduce visual

encoder has backward compatibility with JPEG

distortion of the reconstructed image is explained

decoder. At the steganographic decoder, thein Section 4. The performance evaluation on 4K

enhancement codes can be extracted from lower

standard test images is demonstrated in Section 5,

DCT coefficients to reconstruct higher DCT

and conclusions are given in Section 6.

coefficients. As a result, the steganographic

2. SYSTEM CONFIGURATION

decoder obtains high-resolution images, while
standard JPEG decoder obtains only low-resolution

Figure 1 shows the basic configurations ofimages (1/2 lower resolution in horizontal andsteganographic encoder and decoder thatvertical directions).

adaptively determines run-length Huffman codes

As the distortion due to steganographic

from higher DCT coefficients according to thecoding should be as low as possible, the amount

payload constraint of lower DCT coefficientsof enhancement codes embeddable to lower DCT

while conforming to JPEG specification. The

coefficients has an upper limit called payload. The

steganographic encoder embeds the enhancement

conventional method determines the number ofcodes into LSBs of 8×8 lower frequency quantizedhigher DCT coefficients for creating enhancement

DCT coefficients, and the steganographic decoder

codes in advance not to exceed the payload: thisextracts the codes from LSBs of the lower DCT

determination method uses the constant number ofcoefficients to reconstruct high-resolution images.

scans for higher DCT coefficients in all the blocks.

Standard JPEG decoder also can recover output

However, it cannot utilize the inherent payload

images in spite of half the resolution of thoseefficiently because the constant number of scansfrom the steganographic decoder. Therefore, thismust be determined at the most severe DCT blocksteganographic image compression method hasin regard to the total length of enhancement codes

backward compatibility with JPEG. The buildingin that block. Moreover, the permissible number

blocks, numbered (1) to (5), in this figure performof scans can vary among images, and this number

the following tasks.

needs to be transmitted to the decoder by a certain(1) Compute 16×16 DCT coefficients of highresolution original input image.

way. If the number of higher DCT coefficientsembedded into lower DCT ones can change(2) Quantize 8×8 lower DCT coefficients with aadaptively for every DCT block to make full use

quality factor QF 1, and then compute payloadof the payload without needing side information

PL from the quantized DCT coefficients.
(3) Quantize 16×16 higher DCT coefficients withto the decoder, it will be expected that the quality― 64 ―Steganographic Image Compression Method with Adaptive Enhancement Code Embedding and Its Performance Evaluation on 4K Standard Test Images

Fig. 1

Steganographic image encoder/decoder configurations with adaptive determination of enhancement codes.

a quality factor QF 2.

A larger QF creates smaller step size, so this(4) Extract 16×16 higher DCT coefficients

leads to smaller quantization distortion. Hence, theaccording to the maximum number of scans

payload PL is determined by the quality factor

SC , and adaptively create enhancement codes
based on the payload PL from part (2).
(5) Embed the enhancement codes into 8×8
lower DCT coefficients, and encode the DCT
coefficients according to JPEG entropy coding.
In this image compression algorithm, there arethree parameters that mainly control the qualityof decoded images: quality factors QF 1 and QF 2
for quantizing lower and higher DCT coefficients,
respectively, and the number of scans SC forhigher DCT coefficients using L-shaped scan (asshown in figure 2). If the initial step size of thequantizer for DCT coefficients is B i , actual step
size of the quantizer, Ai , is determined by thequality factor QF (QF 1 or QF 2), and it is given by

QF 1 of lower DCT coefficients, and PL increases
for larger QF 1. Figure 2 schematically shows how
the determination and embedding of enhancement
codes relate to these three parameters that play animportant role in controlling image quality. Here,the DC component in lower DCT coefficients is

whereFig. 2― 65 ―

Enhancement code creation and LSB embedding.

Isao FURUKAWA and Junji SUZUKI

disregarded form the payload computation because

the payload must be greater than or equals to 4 inthe bit-embedding into DC component yields

order to embed the enhancement codes, just only

significantly large image quality degradation.

EOB code is also permitted. On the other hand,

In implementing this processing, there are

the steganographic decoder can recognize whether

several key points that must be taken into

DCT coefficients contain only DC component or

consideration. These points relate the fact that

not when the payload is computed, and if nothing

the JPEG codestream has two special run-length

but DC component exists in the lower frequency

Huffman codes: one is 4-bit EOB (end of block)quantized DCT coefficients, condition 2 is regarded

code that indicates the end of entropy codes for aas condition 1 because it is impossible for the

DCT block, and another is 11-bit ZRL (zero run-decoder to discriminate between them in thislength) code that indicates 16 consecutive zeroes.

configuration. Therefore, when conditions 1 orFirstly, there is a special case that EOB code is

3 are satisfied, the steganographic decoder does

regarded to exist implicitly by comparing the

not proceed to extract enhancement codes, andamount of enhancement codes and the payload,reconstructs higher DCT coefficients as if thereeven though EOB code is not actually embedded.

exists EOB code alone. When both the conditions

Secondly, it is necessary to truncate run-length

1 and 3 are not satisfied, the steganographic

Huffman codes when the total length of the codes

decoder extracts enhancement codes and recovers

is greater than the payload. The enhancement

higher DCT coefficients. As explained before, thecodes after truncation must conform to the rule

extracted enhancement codes can be just only

defined by the run-length Huffman coding of JPEGEOB code. In such a case, recovered higher DCT

as if this encoding process is terminated before

coefficients are all zeroes.

arriving at the payload limit. For example, an EOB

Based on the above discussion, the conditions

code just after ZRL is not allowed by the rule ofthat enable embedding/extraction of enhancement

run-length Huffman coding.

code in encoder/decoder can be tabulated as Table

Now we consider necessary conditions

1 in terms of the lower frequency quantized DCT

whether enhancement codes are embeddable orcoefficients and the payload.

not for a given set of quantized DCT coefficients,

Table 1enhancement codes, and the payload. The adaptive

Possible processing in encoder and decoder.

Exist only DC coefficient
PL < 4
Exist non-zero
AC coefficients
PL ≥ 4

method to truncate the enhancement codes will be
described in Section 3. The conditions that allow
bypassing from enhancement code determination
to LSB embedding in the steganographic encoder

Condition 1
Condition 3
Embed (in encoder)/Extract (indecoder) enhancement codes

3. ADAPTIVE CODE DETERMINATION

fall into following three categories [4].
Condition 1: Only DC coefficient exists in lower

Adaptive determination of enhancement codes

frequency quantized DCT coefficients, and thecan be realized by shortening the length of codes

length of enhancement codes equals to 4.

below the payload of each DCT block. If non-zero

Condition 2: Only DC coefficient exists in lower

AC coefficients exist in lower frequency quantizedfrequency quantized DCT coefficients, and theDCT coefficients, this adaptation starts with, in

length of enhancement codes is greater than 4.

accordance with the results shown in table 1,

Condition 3: Non-zero AC coefficients exist in

categorizing two inevitable cases as follows, where
CE is the length of enhancement codes, and PL is
the payload.
・ If PL < 4, encoder does not embed enhancement
codes, and decoder reconstructs higher DCT
coefficients as if there exists only EOB code. In
this case, all the higher DCT coefficients are set

lower frequency quantized DCT coefficients, andthe payload is less than 4.
The adaptive method to determineenhancement codes in the steganographic
encoder truncates the codes while the length ofenhancement codes is greater than the payload. As― 66 ―Steganographic Image Compression Method with Adaptive Enhancement Code Embedding and Its Performance Evaluation on 4K Standard Test Images

steganographic encoder, where NC is the number

to zeroes.
・ If PL ≥ 4, encoder truncates enhancement codesof run-length Huffman codes, MC [ i] is the length

until the condition of PL ≥ CE is satisfied, andof i- th code, and F Z [ i] is a flag for discriminating

decoder reconstructs higher DCT coefficients

whether i-th code is ZRL. If i-th code is ZRL, thenaccording to normal decoding procedure. In thisF Z [ i] = 1, and otherwise F Z [ i] = 0. The length ofenhancement codes, CE , is given bycase, enhancement codes after truncation must
conform to the rule of JPEG run-length Huffman
coding.
The final run-length Huffman code in a block

If PL < CE , and further if PL < CE +4 or F Z [N C ]must not be EOB if and only if the last DCT= 1, the last enhancement code with M C [N C ] bits

coefficient in the scan order is not zero. Moreover,already created at this point is discarded because

the enhancement codes after truncation must be

there is no room for concatenating an EOB code

terminated using EOB whatever the last codeat the end. The resulting valid length and number,before truncation is, because they are decoded

CE and N C , of enhancement codes are replaced by
CE-M C [N C ] and N C -1, respectively. Then, if N C = 0,
the enhancement code is only EOB because all thecodes are exhausted by discarding. It is possible to
add EOB code alone, since this truncation process
is originally introduced in case of PL ≥ 4. If N C > 0,
the process returns to the start point for judging
whether EOB code can be concatenated.
This process repeats while EOB code cannot
be concatenated due to the relations among
the payload, the length of enhancement codes,
and the flag of ZRL code discrimination. If PL≥ CE +4 and F Z [N C ] = 0, the enhancement codes
can be terminated by concatenating an EOB asa final code, and at the same time, the number ofenhancement codes, N C , is incremented by 1, thenthe length of enhancement codes and the flag of
ZRL code discrimination become M C [N C ] = 4, F Z [N C ]= 0, respectively, in order to reflect the EOB code
concatenation.

thereafter by JPEG run-length Huffman decoding.
Furthermore, the final truncated enhancement code
cannot be either ZRL or a code corresponding to apair of non-zero AC coefficient and zero run-length
because the decoder fails to recover the correct
number of higher DCT coefficients. Incidentally,
when low frequency quantized DCT coefficientscontain just only DC component (condition 1),
decoding process is completely the same as theprocess in which non-zero AC coefficients exist
and relation of PS < 4 is satisfied (condition 3).
Figure 3 shows a flowchart of the adaptivealgorithm for truncating enhancement codes in the

4. EMBEDDING ORDER FOR CODE BITS
The perceptibility of changes in individual DCT
coefficients was studied by Watson [5], and theresult has been applied to digital watermarking
or steganography in order to reduce the visual
distortion by bit-embedding to DCT coefficients.
This model controls the visual distortion due to
bit-embedding into LSBs of 8×8 DCT coefficients
based on a baseline frequency sensitivity thresholdtb (i, j) (0 ≤ i, j ≤ 7) derived from contrast sensitivity
as well as luminance masking and contrast
Fig. 3masking [6].

Algorithm for truncating enhancement codes.
― 67 ―

Isao FURUKAWA and Junji SUZUKI

Although the baseline contrast sensitivity

LSB plane is at most±2n. The distortion added

provides an estimate for the threshold based on

to reconstructed DCT coefficients is obtained by

HVS (human visual system), it needs to combine

summing the distortion on LSB planes multiplied

several distortion measures into a single perceptual

by the quantizer step sizes. When this distortion is

distance using DC component of individual DCT

added to output images, the effect is proportional

blocks. Embedding enhancement codes, however,to the power (squared value) of the distortion

is a closed processing in one DCT block, and it

from the view point of SNR, but it is not obvious

is independent of DC components in other DCT

whether the relation holds from the view point ofblocks. Hence, if the baseline frequency sensitivity

HVS.

threshold tb (i, j) is modified by considering DC

We assume that the perceptibility of distortion

component, the order among magnitudes ofis proportional to its magnitude raised to thethe threshold at position (i, j) does not change.

p -th power, where p is some positive constant. If
p is 1, then the perceptibility is proportional tothe amplitude, and if p is 2, then to the squareamplitude. Let dn (i, j) be the perceptibility of
distortion after dequantization at the position(i, j) on n-th LSB plane, and Δ(i, j) be the default
quantization step size of JPEG. Then, dn (i, j) isrepresented as Δ(i, j)·2n raised to the p-th power.
As a result, visual distortion, vd n (i, j), measured
with JND can be represented after dividing theperceptibility of bit-embedding distortion by thefrequency sensitivity threshold:This means that the use of baseline frequency
sensitivity threshold is sufficient to determine theembedding order as far as magnitude order of thethreshold is retained.
Therefore, we will consider a simple methodfor determining bit-embedding order on thepremise that JNDs (just noticeable differences)
for the distortion by bit-embedding are basicallydetermined by tb (i, j). In order to discuss more
precisely, the individual DC components should
be taken into account to derive the perceptual
distance as described above, but the main problem
here is to clarify the bit-embedding order rather
than the allowable number of least significant bits

Hence, if we embed all the enhancement codes

for embedding. The latter problem will be out ofin ascending order of vd n (i, j) one by one (i.e., in

scope in this paper.

ascending order of visual impacts measured by

The distortion of DCT coefficients after

JND), the reconstructed output image is expecteddequantization in the decoder can be evaluatedto have smaller visual distortion for an appropriateby the coefficient times quantizer step size Δ(i, j).

p value.
Table 2 shows, substituting default quantization
step size for luminance components of JPEG toequation (4), the embedding order of enhancement
code bits on 0th to 2nd LSB planes for p = 1 and
2, where 0 is the first and 188 is the last. The DC
component at position (0, 0) is excluded from bitembedding because it leads to large degradationof reconstructed images. It is obvious that the bitembedding to lower DCT coefficients in 0th LSB
plane tends to have higher priority than that tohigher DCT coefficients in the same LSB plane incase of p = 2, since visual distortion exponentially
increases as the frequency of DCT coefficients andthe plane number of LSBs (but this embedding
order is different from zigzag scan order).

Figure 4 shows a decomposition of 8×8 quantized
DCT coefficients into bit planes (only 0th to 2nd
LSB planes are shown). The distortion of quantized
DCT coefficients by embedding one bit on n-th

Fig. 4LSB planes of 8 × 8 quantized DCT coefficients― 68 ―Steganographic Image Compression Method with Adaptive Enhancement Code Embedding and Its Performance Evaluation on 4K Standard Test Images
Table 2

Table 3

Embedding order of enhancement code bits.

Embedding order from 0th to 5th planes (p = 2.0).

embedding order for least significant bits from 0th
to 5th planes. Then, the total number of candidate
At position (i, j) of the LSB planes, lower plane

bits for embedding enhancement codes is 63×

is selected prior to higher plane because the

6 = 378 except for DC component, so we create

perceptual distortion due to bit- embedding, dn

an array of embedding order consisting of 378(i, j), always satisfies the relation dn (i, j) < dm(i, j)elements. If the position (i, j) on an LSB plane

for n < m (i.e., the embedding order in lower LSB

corresponds to a value of i+8 j, elements of theplane is earlier than that in higher LSB plane atarray are represented with numbers 1 throughthe same position (i, j)). Hence, when we create a63, where each number appears just six times.

table of bit-embedding order, it is not necessary to

For example, Table 3 shows the array for bit-indicate explicitly which LSB plane the embedding

embedding order from 0th to 5th LSB planes withorder corresponds to. More specifically, althoughp = 2. In this array, the first and second numbersare‘2’and‘9’, so these numbers correspond topositions (i, j) = (2, 0) and (1, 1), respectively. On
the other hand, in table 2 for p = 2, the numbers‘0’at position (2, 0) and‘1’at position (1, 1) on
0th LSB plane indicate the first and second bits
for embedding enhancement codes, respectively,
so that there is no contradiction between thenumbers of tables 2 and 3in their meanings.

numbers from 0 to 63 appears several times (thenumber of LSB planes), firstly appeared number
corresponds to the bit on 0th LSB plane, and when
the same number appeared again, it corresponds
to the bit on 1st LSB plane, and so on. There is noambiguity in the embedding order sequence.
The LSB planes of quantized DCT coefficientswith 10-bit precision consist of 0th to 9th planes,
and the number of embeddable bits to each DCT

5. PERFORMANCE EVALUATION

coefficients is determined by the amplitude of thecoefficient. In this case, the maximum theoretically

5.1 SCANNING METHODS

embeddable number of bits is nine, but here it is

The conventional steganographic encoder utilizes

restricted to six considering the image quality

the constant number of scans for higher DCT

degradation.

coefficients in all the blocks when enhancement

When the enhancement codes are embedded

codes are created by run-length Huffman encoding,up to six LSB planes, we must determine the bit-although the proposed steganographic encoder― 69 ―

Isao FURUKAWA and Junji SUZUKI

adaptively changes the number of scans (moresets, the quantitative results for only u01 and u04

precisely, the length of enhancement codes) based

images are shown here, and for the rest of the images,on the payload of each DCT block. Moreover,

u02 and u03, we make some comments if necessary.

the proposed method employs, for embedding

Figure 5 shows SNRs of low- and high-enhancement codes into low frequency quantized

resolution reconstructed images obtained from the

DCT coefficients, HVS-based order rather thansteganographic decoder using conventional zigzag

zigzag scan order to reduce the visual distortion

scan order and the proposed HVS-based order fordue to bit-embedding. In order to evaluate thebit-embedding. The color decimation format is 4:4:4,

performance of the proposed method on 4K

and the quality factor QF 1 for quantizing lower

standard test images [7], we prepared 4K images

DCT coefficients is fixed to 95. These results showobtained from a color gamut conversion fromthat the SNRs are higher in the following order forRec.2020 to Rec.709 followed by bit reduction

both low-resolution JPEG decoded images and high-from 12 to 8 bits. Although the evaluation was

resolution enhanced images: HVS-based (p =1.0) <carried out against four images of u01_Books, u02_

zigzag < HVS-based (p =2.0). In this figure, SNRs ofMusicBox, u03_Moss, and u04_Kimono in the test

low-resolution JPEG decoded images monotonicallyFig. 5

SNR of low- and high-resolution reconstructed image with zigzag and HVS-based embedding orders (QF1 = 95).

― 70 ―Steganographic Image Compression Method with Adaptive Enhancement Code Embedding and Its Performance Evaluation on 4K Standard Test Images

decrease with QF 2 because the amount of

the number of scans SC and the quality factor

enhancement codes increases in lower DCT

QF 2 used in higher DCT coefficient processing.
It is possible for the steganographic encoder
to embed more enhancement codes when theadaptive determination method for the codes isincorporated, and the same ratio in this case isshown in the figure by extending the solid lines
with broken lines. These results are obtained using
the same zigzag scan for bit-embedding as theconventional method. Of course, the conventional
method cannot attain the amount of enhancement
codes shown with these broken lines.
If the number of scans is increased under thecondition of constant method, the steganographic
encoder fails to embed enhancement codeswhen the quality factor QF 2 is relatively large.
Moreover, if the quality factor QF 1 is smaller than95, the embeddable condition becomes more severe
because of payload reduction (not shown here).
On the other hand, the symbols‘－’in the figure
show the ratios for adaptive determination methodwith QF 1 = 50, 55, 60, ..., 95, and of these, only theratios for QF 1 of 95 are connected with a solidline. It is obvious that the adaptive determination
method enables to embed much more enhancement
codes than the conventional constant method forthese images. For mage u03, lower frequency
is dominant, and there exists a combination ofparameters that can embed the enhancement
codes up to 5 scans even for the constant method.

coefficients and greater amount of codes leads tolarger distortion. As for high-resolution enhanced
images, SNRs increase with QF 2 in smaller QF 2
region because the quality of decoded images isdetermined mainly by the reproducibility of higher
DCT coefficients rather than the additional noise inlower DCT coefficients. On the other hand, SNRs
decrease with QF 2 in larger QF 2 region because
the distortion due to LSB embedding becomesdominant compared with the quality improvementby high frequency augmentation. As a result, SNR
curves of high-resolution enhanced images have
convex shapes, and there is an optimum QF 2 thatmakes SNR maximum for a given QF1. In the caseof these two images with QF 1 of 95, the optimum

QF 2 is about 70. Incidentally, the optimum QF 2 isalso about 70 for image u02, while it is about 80 for
image u03.
5.2 AMOUNT OF ENHANCEMENT CODES
Figure 6 shows the ratio between the amountof enhancement codes and that of JPEG codeswith QF 1 = 95. In the conventional method withconstant number of scans, there always exist
inconvenient cases where enhancement codes
cannot be embedded by the payload constraint,
and the codes can only be embedded for solid lines
indicated with‘constant’for the combination ofFig. 6

Ratio between total amount of enhancement codes and that of JPEG codes.

― 71 ―

Isao FURUKAWA and Junji SUZUKI

Fig. 7

SNR of high-resolution reconstructed image with constant number of scans.

Fig. 8

SNR of high-resolution reconstructed image with adaptive scanning.

5.3 SNR FOR CONSTANT SCANNING

higher than that for the adaptive scanning method.

Figure 7 shows SNRs for high-resolution
reconstructed images in the steganographic

5.4 SNR FOR ADAPTIVE SCANNING

decoder with constant number of scans by solid

Figure 8 shows SNRs for high-resolutionlines. SNRs with adaptive number of scans arereconstructed images with adaptive scanningalso shown in the figure by extending the solidusing QF 1 = 50, 55, 60, ..., 95, where the maximum

lines with broken lines in a similar fashion as

number of scans is set to eight. This means that at

figure 6. Although SNR increases as the number

most 8 scans are possible according to the payload,of scans SC and the quality factor QF 1 increase in

and in fact, the number of scans is not always

almost all cases, the conventional steganographic

eight mainly because of the payload constraint. (Itencoder with constant scanning fails to embedis possible that the higher frequency quantizedenhancement codes before arriving at the

DCT coefficients are almost zeroes for relatively

maximum SNR because of the payload constraint.

flat image regions.)

For image u03, however, there is a combination of

In general, SNR curves have convex shapes

parameters where the maximum SNR attainable

when the low frequency quality factor, QF 1, isfor the conventional constant method is slightly

greater than 80 or 85, and there exists the high― 72 ―Steganographic Image Compression Method with Adaptive Enhancement Code Embedding and Its Performance Evaluation on 4K Standard Test Images

frequency quality factor, QF 2, that maximizes(in vertical)) DCT blocks. The number of scans

SNR. These curves are monotonically decreasingthat makes SNR maximum for constant scanningwith QF 2 when QF 1 is smaller than about 75.

is 1 for image u01 and 2 for image u04, and it is

These results for QF 1 of 95 are already shown

impossible to embed any more enhancement codesin figure 5. For images other than u03, maximum

for these images. The amount of embeddable

SNRs in figure 8 are higher than that in figure

enhancement codes with adaptive scanning

7 for all parameter combinations. That is, thebecomes two to three times that with constantadaptive scanning can provide higher SNR thanscanning, and the adaptive steganographic encoder

the constant scanning. For image u03, however,

never fails to embed these codes.

SNR for the constant scanning with SC =2 isFigure 9 shows the enhancement code bits

slightly higher than that for the adaptive scanningper DCT block for both constant and adaptive

with setting maximum SC to eight.

scanning methods as images in monochrome tone,

5.5 DISTRIBUTION OF ENHANCEMENT CODES

Table 4 Amount of enhancement codes at maximum SC . Codebits per block in parenthesis for adaptive scanning are values
before truncating these codes.

Table 4 shows parameter combinations that makethe amount of enhancement codes maximum
for constant scanning, as well as its maximum

Constant

value. For making a comparison, this table also
includes results for adaptive scanning in the same
parameter conditions. The enhancement code bits

Adaptiveper block in parenthesis for adaptive scanning arethese values before code truncation. Note that the
total length of codes is shown in bytes by summing
up for 32,400 (i.e., 3840/16 (in horizontal)×2160/16

Fig. 94K image(QF 1, QF 2)SC
Mean
Code bitsMax
per blockMin
Total code bytes
SC
Mean
Code bitsMax
per blockMin
Total code bytes

u01_Books(95, 85)
1
17.6
73
4
71,232
8
61.1 (142.6)
218 (687)
4 (4)247,559

Enhancement code bits per DCT block (value of 255 is most highlighted).
― 73 ―

u04_Kimono(95, 70)
2
13.8
116
4
55,69927.5 (43.2)
226 (462)
4 (4)111,335

Isao FURUKAWA and Junji SUZUKI

where the value of 255 is most highlighted. Thisaccording to the HVS-based order. High-resolution

figure clearly indicates that more enhancement

decoded images obtained from the conventional

codes, which are impossible to be embedded bymethod with constant scanning are also shown as

the constant scanning, become embeddable by thea reference.

adaptive scanning. Results for images u02 and u03

In the following, we make some comments forare analogous to this figure.

individual 4K images. The image u01 contains
many characters on the spine of books, so high

5.6 DECODED IMAGES

frequency components from these edges yieldNow we compare the actually decoded images

large distortion. Readability of the characters is

by using both steganographic decoder and JPEG

higher in the image obtained from the adaptive

decoder. The steganographic encoder determines

scanning than that from constant scanning because

enhancement codes by either constant or adaptive

much of high frequency components are preserved

scanning methods. These examples are images

in the former image.

only obtained using a parameter combination that

The image u02 is a combination of small

makes SNR for each scanning method maximum.

regions that contains more high frequency andHere, a small region with 240×180 pixels is clipped

less high frequency components. Although thefrom a whole decoded image as a representative,

adaptive scanning is superior to the constantand such regions of images are compared side byscanning for most areas in the image, relatively

side, since the images with entire size are difficult

flat regions such as the face of doll contain large

to recognize how much they are distorted. The

low frequency distortion caused by embedding theupper left coordinates of these clipped regions

enhancement codes into lower DCT coefficients.

are (1500, 1000) for image u01 and (1650, 1050) forIn such cases, the maximum number of scans forimage u04, respectively.

higher DCT coefficients or the payload should be

Table 5 shows parameter sets that makerestricted appropriately.

SNRs maximum for both constant and adaptive

The image u03 has smallest high frequency

scanning methods, SNRs for high-resolution images

components among the images tested here, sofrom the steganographic decoder, and SNRs

it has large payload for lower DCT coefficients.

for low-resolution images from JPEG decoder.

This image has slightly higher SNR when

In computing SNRs of low-resolution images,

constant scanning rather than adaptive scanningreconstructed images using 8×8 inverse DCT of 8

is employed, but on the contrary, it seems that

×8 DCT coefficients from original high-resolution

the visual quality of adaptive scanning is slightly

images are used as reference images.

improved compared to that of constant scanning.

Table 5Constant Adaptive

SNR

SNR

In this case, the SNR measurement may not be

Parameter sets at maximum SNR.

4K image(QF 1, QF 2)
SCHigh resolution
Low resolution(QF 1, QF 2)
SCHigh resolution
Low resolution

u01_Books(95, 65)2
28.35 dB
44.58 dB
(95, 70)

appropriate to evaluate image quality.

u04_Kimono(95, 70)2
30.46 dB
46.40 dB
(95, 70)

The image u04 has higher frequency
components in the texture of cloth than the
background, and it can be observed that thevisual resolution for adaptive scanning is higher

8
29.24 dB
37.76 dBthan that for the constant scanning. The low

31.05 dB
38.44 dB

frequency distortion found in the case of image
u03 is scarcely perceptible in image u04. It is mostFigure 10 shows original and decoded images

obvious that the high-resolution images obtained(clipped) together with a simplified encoder/from the steganographic decoder can attain higher

decoder configuration found in figure 1. Here,visual resolution than low-resolution images fromthe enhancement codes are determined by the

JPEG decoder for all the images tested here.

proposed adaptive scanning, and then embedded― 74 ―Steganographic Image Compression Method with Adaptive Enhancement Code Embedding and Its Performance Evaluation on 4K Standard Test Images

Fig. 10 Comparison of original image, high-resolution images reconstructed with constant and adaptive scanning methods, and lowresolution JPEG decoded image (240 × 180 pixels).

― 75 ―

Isao FURUKAWA and Junji SUZUKI

number of scans need not to be a common value

6. CONCLUTION

in a whole image: the amount of embeddable codes

In JPEG-based image enhancement coding withto lower DCT coefficients is determined by thesteganographic data embedding, we proposed adaptive

payload together with the amount of enhancement

method that can make the amount of enhancement

codes, and also a set of the enhancement codes

codes maximum based on the payload of low frequency

must be terminated with an EOB after truncation

quantized DCT coefficients. We also proposed HVS-

so as not to exceed the payload of individual blocks.

based order for embedding enhancement codes into

Hence, the allowable number of scans in a block is

LSBs of lower DCT coefficients. The performancea parameter specific to that block, and it need notof the adaptive steganographic image compression

to be transmitted to the steganographic decoder.

method was evaluated using four 4K standard test

Our future topic is to clarify the relation between

images obtained from transforming Rec.2020 color

image contents and the allowable number of scans for

gamut to Rec.709 together with truncating 12 to 8 bits.

enhancement codes in the steganographic encoder.

Note that these four test images do not correspond

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