BTC-VQ-DCT hybrid coding of digital images

Wu, Yulin; Coll, D.C.

doi:10.1109/26.99132

Cited by 44 publications

(11 citation statements)

References 13 publications

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“…All the experimental results are illustrated at the end of paper and a comparison with various techniques is also given. The performances of the proposed methods are compared with that of the BTC [15], BTC-VQ [16], BTC-DCT [17], BTC-VQ-DCT [17], BTC-PVQ-DCT I [18] , BTC-PVQ-DCT II [18] method in terms of bit per pixel rate and coding quality for the average values of four images as listed in Tables I. Table II shows the compression ratio is better than JPEG and PSNR value of decompressed image is comparable to JPEG.…”

Section: Resultsmentioning

confidence: 99%

An Efficient Image Compression Algorithm Based on Histogram Based Block Optimization and Arithmetic Coding

Dutta¹,

Abhinav²,

Dutta³

et al. 2012

IJCTE

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Abstract-The need for an efficient technique for compression of Images is ever increasing because the raw images need large amounts of disk space seems to be a big disadvantage during transmission and storage. In this paper, an efficient algorithm has been proposed for lossy image compression/decompression scheme using histogram based block optimization and arithmetic coding. Experimental result shows that the proposed algorithm gives better compression ratio as that of JPEG and some other techniques and PSNR value of decompressed image is comparable to JPEG.

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Section: Resultsmentioning

confidence: 99%

An Efficient Image Compression Algorithm Based on Histogram Based Block Optimization and Arithmetic Coding

Dutta¹,

Abhinav²,

Dutta³

et al. 2012

IJCTE

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“…For a 512x512 input image with 4x4 blocks, The size of a subimage is 128x128. Several methods for coding the quantization data have been proposed in the literature, including the fixed number of bits, vector quantization (Udpikar and Raina, 1987), DCT (Wu and Coll, 1991), and lossless coding (Franti and Nevalainen, 1995). The subimages have details and important features that must be preserved.…”

Section: Reduction Of the Quantization Datamentioning

confidence: 99%

Bit rate reduction techniques for absolute moment block truncation coding

Chen¹,

Tai²

1999

Journal of the Chinese Institute of Engineers

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Block Truncation Coding uses a two-level moment preserving quantizer that adapts to local properties of the images. It has the features of low computation load and low memory requirement while its bit rate is only 2.0 bits per pixel. A more efficient algorithm, the absolute moment BTC (AMBTC) has been extensively used in the field of signal compression because of its simple computation and better MSE performance. We propose postprocessing methods to further reduce the entropy of two output data of AMBTC, including the bit map and two quantization data (a, b). A block of a 2×4 bit map is packaged into a byte-oriented symbol. The entropy can be reduced from 0.965 bpp to 0.917 bpp on average for our test images. The two subimages of quantization data (a, b) are postprocessed by the Peano Scan. This postprocess can further reduce differential entropy about 0.4 bit for a 4×4 block. By applying arithmetic coding, the total bit reduction is about 0.3~0.4 bpp. The bit rate can reach 1.6~1.7 bpp with the same quality as traditional AMBTC.

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“…However, the image quality obtained by the traditional BTC degrades rapidly with the increase of the coding gain. Several investigations have addressed in the issue of further improving the image quality or coding gain of the BTC [2]- [6], Some of those include using vector quantization (VQ) to further compress the overhead information of the BTC outputs [2]; applying a hybrid coding model by using the LUT-based VQ to fast encode the bit-map, and the DCT to encode the high-mean and low-mean subimages [3]; adopting universal Hamming codes and a differential pulse code modulation (PCM) to the bit plane and the side information of BTC to reduce bit rate and preserving the low computational complexity [4]; using moment and visual information content to determine the regions for further BTC processing or neglecting in order to reduce the computation overhead, which preserves moderated quality while remaining the possibility of real time processing [5]; employing two-step criterion to determine if a block is encoded with neighboring coded blocks, block mean, or moment preserving BTC [6] in order to reduce the bit rate of the BTC scheme.…”

Section: Introductionmentioning

confidence: 99%

Quality Compressed Steganography Using Hidden Referenced Halftoning

Guo

Chen

2007

Ninth IEEE International Symposium on Multimedia (ISM 2007)

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Block truncation coding is an efficient compression technique while offering good image quality. Nonetheless, the blocking effect inherent in BTC causes severe perceptual artifact in high compression ratio applications. In this paper, an Error-Diffused Block Truncation Coding (EDBTC) is proposed to solve this problem. According to the EDBTC, the error caused by the difference between the original grayscale pixel value and the correspondingly high or low mean substitute is diffused to the predefined neighborhood, and hence the average grayscale will be maintained invariably. In addition, since the compressed data are widely distributed in the internet transmission, the extra message delivering in a secret way also highly raises attention recently. In this paper, we propose the Compressed Steganography using Hidden Referenced Halftoning (CSHRH), which cooperates with error diffusion and ordered dithering to achieve the objective of secret communication in BTC images. As documented in the experimental results, a low complexity with good image quality approach is obtained. Moreover, CSHRH is extended to Secret-Sharing Steganography (SSS) and Color Extension Steganography (CES). The SSS is able to distribute message into multiple host images and hence improves the security. The CES is able to deliver secure message via color embedded CSHRH image. Both extensions are also with an extra benefit of achieving high capacity message convection.Key words: block truncation coding, steganography, error diffusion, ordered dithering, secret sharing INTRODUCTIONBlock truncation coding (BTC) was first introduced by Delp and Mitchell in 1979 [1]. The basic concept is to divide the image into non-overlapped blocks, each pixel in a block is replaced by either high or low mean while preserving the first and second moments of the block. The main advantages of the method are the good image quality and the relatively lower complexity compared to the modern compression techniques, e.g. JPEG or JPEG2000. However, the image quality obtained by the traditional BTC degrades rapidly with the increase of the coding gain. Several investigations have addressed in the issue of further improving the image quality or coding gain of the BTC [2]-[6], Some of those include using vector quantization (VQ) to further compress the overhead information of the BTC outputs [2]; applying a hybrid coding model by using the LUT-based VQ to fast encode the bit-map, and the DCT to encode the high-mean and low-mean subimages [3]; adopting universal Hamming codes and a differential pulse code modulation (PCM) to the bit plane and the side information of BTC to reduce bit rate and preserving the low computational complexity [4]; using moment and visual information content to determine the regions for further BTC processing or neglecting in order to reduce the computation overhead, which preserves moderated quality while remaining the possibility of real time processing [5]; employing two-step criterion to determine if a block is encoded with neighboring coded blocks,...

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BTC-VQ-DCT hybrid coding of digital images

Cited by 44 publications

References 13 publications

An Efficient Image Compression Algorithm Based on Histogram Based Block Optimization and Arithmetic Coding

An Efficient Image Compression Algorithm Based on Histogram Based Block Optimization and Arithmetic Coding

Bit rate reduction techniques for absolute moment block truncation coding

Quality Compressed Steganography Using Hidden Referenced Halftoning

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