Аdaptive combined image coding with prediction of arithmetic code volume

The problem of increasing the efficiency of coding of halftone images in the space of bit planes of differences in pixel values obtained using differential coding (DPCM – Differential pulse-code modulation) is considered. For a compact representation of DPCM pixel values, it is proposed to use a combined compression encoder that implements arithmetic coding and run-length coding. An arithmetic encoder provides high compression ratios, but has high computational complexity and significant encoding overhead. This makes it effective primarily for compressing the mean-value bit-planes of DPCM pixel values. Run-length coding is extremely simple and outperforms arithmetic coding in compressing long sequences of repetitive symbols that often occur in the upper bit planes of DPCM pixel values. For DPCM bit planes of pixel values of any image, a combination of simple run length coders and complex arithmetic coders can be selected that provides the maximum compression ratio for each bit plane and all planes in general with the least computational complexity. As a result, each image has its own effective combined encoder structure, which depends on the distribution of bits in the bit planes of the DPCM pixel values. To adapt the structure of the combined encoder to the distribution of bits in the bit planes of DPCM pixel values, the article proposes to use prediction of the volume of arithmetic code based on entropy and comparison of the obtained predicted value with the volume of run length code. The entropy is calculated based on the values of the number of repetitions of ones and zero symbols, which are obtained as intermediate results of the run length encoding. This does not require additional computational costs. It was found that in comparison with the adaptation of the combined encoder structure using direct determination of the arithmetic code volume of each bit plane of DPCM pixel values, the proposed encoder structure provides a significant reduction in computational complexity while maintaining high image compression ratios.

A Dynamic Steganography Method for Web Images with Average Run-Length-Coding

Web page has many redundancies, especially the dynamic html multimedia object. This paper proposes a novel method to employ the commonly used image elements on web pages. Due to the various types of image format and complexity of image contents and their position information, secret message bits could be coded to embed in these complex redundancies. Together with a specific covering code called average run-length-coding, the embedding efficiency could be reduced to a low level and the resulting capacity outperforms traditional content-based image steganography, which modifies the image data itself and causes a real image quality degradation. Our experiment result demonstrates that the proposed method has limited processing latency and high embedding capacity. What’s more, this method has a low algorithm complexity and less image quality distortion compared with existing steganography methods.

Run length coding and efficient compression of hexagonal raster data based on Gosper curve

<p><strong>Abstract.</strong> Compared with regular quadrilateral grid, regular hexagonal grid is isotropy and has higher cell compactness and sampling density. This gives regular hexagonal grid advantages in visual display, spatial analysis, and many other aspects. However, the studies of raster data mainly focus on regular quadrilateral grid, and various encoding methods are also focused on it. The researches on hexagonal raster data are relatively insufficient.</p><p>In this paper, encoding and compression for regular hexagonal grid are studied. By introducing Gosper curve which has good spatial aggregation and takes into account the morphological structure of regular hexagonal grid, the bidirectional correlation between Gosper curve and regular hexagonal grid is established. Then, a new encoding framework is built to determine the Gosper coding of each grid unit. The lossless compression is completed by performing run-length coding on adjacent coding sets in the target region.</p>

Test Data Compression with Alternating Equal-Run-Length Coding

This paper presents a new X-filling algorithm for test power reduction and a novel encoding technique for test data compression in scan-based VLSI testing. The proposed encoding technique focuses on replacing redundant runs of the equal-run-length vector with a shorter codeword. The effectiveness of this compression method depends on a number of repeated runs occur in the fully specified test set. In order to maximize the repeated runs with equal run length, the unspecified bits in the test cubes are filled with the proposed technique called alternating equal-run-length (AERL) filling. The resultant test data are compressed using the proposed alternating equal-run-length coding to reduce the test data volume. Efficient decompression architecture is also presented to decode the original data with lesser area overhead and power. Experimental results obtained from larger ISCAS'89 benchmark circuits show the efficiency of the proposed work. The AERL achieves up to 82.05 % of compression ratio as well as up to 39.81% and 93.20 % of peak and average-power transitions in scan-in mode during IC testing.