Method for transferring additional information during fractal encoding of image

FIELD: electric communications, namely, communications with decreased excessiveness of transferred information.

SUBSTANCE: in accordance to method, during encoding of image by means of method of fractal compression, into lower bits of domain indexes, additional information is inserted. To remaining bits of indexes of source image domain, sample inversion procedure is applied. After building in additional information and optimization of domain indexes these data together with information about domain orientation indexes, brightness and contrast are transferred via communication channel. At receiving side, additional information is separated and original image is restored.

EFFECT: transfer of additional information.

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The invention relates to telecommunications, and in particular to the field associated with the reduction of the redundancy of the transmitted information. The reason for this is essentially that, with the help of modern technology coding and data compression can significantly reduce the frequency range required for image transfer. The technical result of the invention is to develop a method for the transmission of additional information when encoding images.

The transmission of additional information is performed as follows. When encoding an image using fractal compression method in the low-order bits of the index domain is inserted additional information. The remaining bits of the index domain of the original image is the procedure in the trial of inversion. After embedding additional information and optimizing indexes, domains, these data, together with information about the indexes orientation domains, brightness and contrast are transmitted over the communication channel. At the receiving side there is a selection of additional information and restore the original image.

In digital video technology to increase the transmitted amount of information has already been proposed to replace the digital signal scan data contained in the interval blanking additional information, nab is emer, digital audio signals and to transmit additional information (Ulrich Schmidt, Digital video equipment. Publisher Franzis Verlag, Feldkirchen, 1996) [1].

The closest in technical essence to the claimed method for the transmission of additional information in the image coding method is described in patent No. 2212769, IPC7N 04 N 7/08 [2]. Prototype method eliminates non-essential part of image information, i.e. physiologically barely or not at all perceive the fine structure of the image, due to irreversible compaction and subsequent decompression of the image signal, i.e. data reduction and thus obtained the free space inserts the useful and control information.

The purpose of this invention to provide a method which allows for the coding of images to convey additional information. This objective is achieved in that when the fractal compression method in the low-order bits of the index domain enter additional information, reducing the list of used domains, which leads to a considerable decrease in the total encoding time. The remaining bits of the applied procedure test inversion.

Consider the algorithm for the transmission of additional information in fractal Kadirova the AI image.

The basic algorithm for fractal image coding is as follows [3]:

1. The original image is divided into nonoverlapping rank blocks. Rank the blocks may be equal, but more often is an adaptive partitioning of variable size blocks. This gives the possibility to closely fill the rank blocks of the small size of the image containing fine detail.

2. Then cover the image sequence domain blocks, possibly overlapping. Domains can be different sizes.

3. The main computational step in fractal coding is a comparison of the domain and rank areas. For each rank of the block, find the domain and the corresponding transformation that best covers the ranking unit. This is usually an affine transformation:

where si- a constant that expands or narrows the range of values of the function f (controls the contrast of the image);

abouti- a constant that increases or reduces the value of the grayscale (controls the brightness of the image);

wi- affine transform;

- spatial component of the transformation wi;

f(x, y) is the pixel value of the image with coordinates (x, y).

An affine transformation which consists of three stages. First, the selected domain is one of the eight basic rotations/reflections (four 90-degree rotation and mirror reflection in each orientation). Secondly, rotating domain region is compressed to fit the size of the rank field. And, finally, by the method of least squares is calculated contrast and brightness corresponding to the optimal values that minimize the expression:

where {dij} and {rij} is respectively the pixel values of the domain and rank areas.

Unfortunately, the computational cost of the search for the required domain among so many options too great. The problem of determining the system domain is a compromise between the necessity to many domains were large enough to allow the selection of the best option, match the rank of the block and, at the same time, small enough so that the search process could be performed in acceptable time. Continue this process until, until you get an acceptable match or the size ranking of blocks reaches a predetermined limit.

In the operation of the basic algorithm, the decoder transmits a domain index, the index of orientation domain, brightness and contrast. In the proposed method, each of the first vector index domains consisting of n bits, are input m bits of additional information instead of the least significant bits of this vector. As a result of this introduction of a list of domains to handle the specific rank of the unit is significantly reduced, resulting in less time finding the right domain, and the total time coding in General. The remaining k=n-m digits of the procedure test inversion.

In this procedure, it is proposed to use a known method Gauss-Seidel [4, s-176]. The process of finding the optimal domain index defined on the set of "1" and "0", it may take quite a long time. Therefore, to reduce the time of searching the optimal elements of the indexes proposed approximate method of search. This method involves the implementation of optimization one subset of the at fixing others. Next, to find the optimal subset, perform the optimization of the other subsets. This process is repeated until the change of one of the subsets will not lead to the minimization (maximization) of the selected criteria.

The process of finding the optimal vector elementsin the proposed method are proposed to be implemented in the form of the following sequence of actions:

1. Put n=1;

2. To generate a vector of domain index, taking into account input more the positive information

3. Put i=1;

4. To choose the appropriate orientation of the domain to calculate the transformation parameters, such as contrast and brightness, and to determine the expressionfor vector;

5. To perform the inversion of the i-th element of the vector:where xi∈{0,1},

6. To form a vector:

7. To choose the appropriate orientation of the domain and configure the conversion settings, such as contrast and brightness, to minimize the expressionin the inversion of the i-th element of the vector;

8. Calculate;

9. Run: if u>0, then the value ofassign the value ofand the value of xiassign; if u<0, then the values of e2and xiremain unchanged;

10. To do: if i<k, then increase i by one and go to step 4; if i=k, then we put n=n+1 and go to step 2 to optimize the following domain index.

After embedding additional information and optimizing indexes, domains, these data, together with information about the indexes orientation domains, brightness and con is lastnosti transmitted over the communication channel. The decoder is the allocation of additional information and restore the original image. The decoding of the image is performed by an iterative application of the affine transformation to an arbitrary initial image. In accordance with theorem on contractive mappings iteration will converge regardless of the choice of the initial image. Compressive mapping is defined as a separate transformation for each rank of the block. Each rank unit has associated with it transformation and domain. The contents of this rank of the block is calculated by applying a transform to the domain block. One iteration is completed when you are ranking the blocks.

The claimed method is illustrated by drawings:

Figure 1 is an affine transformation of the domains that rank in the units;

Figure 2 - insertion of additional information in the basic algorithm of fractal coding;

Figure 3 - procedure record additional information;

Figure 4 - search algorithm is optimal elements of domain indexes when entering additional information for transmission over the communication channel;

Figure 5 - the results of the study when embedding additional information in the domain index.

Figure 1 presents an affine transform domain rank blocks, which consists in fitting the selected domain is the area of the workpiece to rank using eight basic rotations/reflections (four 90-degree rotation and mirror reflection in each orientation).

Figure 2 shows the insertion of additional information in the basic algorithm of fractal coding. In the proposed method, each vector index domains consisting of n bits, instead of the least significant bits are input m bits of additional information, as shown in figure 3. Because these data are not added in addition to the original signal, and replace part of the original signal, the bandwidth of the signal does not increase by adding this information.

Figure 4 presents the algorithm for finding the optimal elements of domain indexes when entering additional information for transmission over the communication channel. After inserting the additional information for the remaining source categories used procedure test inversion, which use a known method Gauss-Seidel for solving optimization problems with a large number of unknowns.

Figure 5 shows the results of the study, which showed that embedding additional information in the domain index the quality of the reconstructed image remains within normal limits. When encoding an image size of 256×256 pixels in grayscale additionally transferred for more information. As additional information is performed, the image 64×64 pixels in grayscale. When decoding : CTCSS / DCS is assured as the initial image was used to the noise. The ratio signal/noise after the fifth iteration for the main image 22.8 dB (restore the main image by iteration presented in figure 5 on the first two rows). When encoding the test image "Lena" without inserting additional information, the ratio of signal to noise was 25,7 dB. The ratio signal/noise after the fifth iteration for additional images was 27 dB (decoding this image presented on the last two rows of figure 5).

BIBLIOGRAPHIC LIST

1. Ulrich Schmidt, Digital video equipment. Publisher Franzis Verlag, Feldkirchen, 1996.

2. Patent No. 2212769, IPC7N 04 N 7/08, bull. No. 26 from 20.09.2003,

3. Swelled. Fractals and wavelets for image compression in action. The tutorial. - M.: Publishing house Triumph, 2003. - 320 S.

4. Rakitin Century. And., Pervushin VE a Practical guide to methods of calculations with application programs for personal computers: Textbook. the allowance. - M.: Higher. HQ., 1998. - 383 S.

Method for the transmission of additional information when encoding images with stage a) digitization of the original image, (b) compression using fractal compression method, (C) insertion of additional information, (d) decompressing the compressed image, (e) the allocation of additional information, characterized in that after the compression of ohodnocovanie using fractal compression method and insert additional information to the remaining source discharges each index of the domains that use the trial procedure of inversion, which use a known method Gauss-Seidel for solving optimization problems with a large number of unknowns, which produce alternating inversion (change "1" to "0" or "0" to "1") of each category of index domains, except for discharges containing additional information when fixing other discharges, resulting in finding the best domain index taking into account the embedded additional information to encode the rank of the block, after which the indexes domains taking into account additional embedded information is transferred over the communication channel.



 

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