Absolute Moment Block Truncation Coding and Its Application to Color Images

Absolute Moment Block Truncation Coding and Its Application to Color Images

Absolute Moment Block Truncation Coding and Its Application to Color Images

Abstract:

A new quantization method that uses the criterion of preserving sample absolute moments is presented. This is based on the same basic idea for block truncation coding of Delp and Mitchell but it is simpler in any practical implementation. Moreover, output equations are those for a two-level nonparametric minimum mean square error quantizer when the threshold is fixed to the sample mean. The application of this method to single frame color images is developed. A color image coding system that uses absolute moment block truncation coding of luminance and chroma information is presented. Resulting color images show reasonable performance with bit rates as low as 2.13 bits/pixel.
Published in: IEEE Transactions on Communications ( Volume: 32, Issue: 10, Oct 1984 )
Date of Publication: 06 January 2003
Print ISSN: 0090-6778
Publisher: IEEE

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RGBW image compression by low-complexity adaptive multi-level block truncation coding

RGBW image compression by low-complexity adaptive multi-level block truncation coding

RGBW image compression by low-complexity adaptive multi-level block truncation coding

Abstract:

Frame memory compression is a widely used image compression technique that aims to reduce the size of the frame memory in display panels such as those containing LCD and OLED technologies. Recent LCD panels use the RGBW color domain to replace the traditional RGB domain in order to enhance the brightness of LCD panels with the addition of a white component. The additional component increases the size of the frame memory but necessitates an aggressive compression algorithm. This paper proposes a novel compression algorithm for RGBW components that improves the efficiency of block truncation coding (BTC), which is widely used for LCD overdrive. The proposed low-complexity adaptive multi-level block truncation coding (LAM-BTC) algorithm codes RGBW color data with a width of ten bits. It adaptively selects two-level BTC or four-level BTC to enhance the quality of the images, for which a low-complex level selection scheme is used. Four-level BTC in the proposed algorithm codes two representative values (RV) in four RVs and infers the other two RVs using inter-color correlation. In spite of the reduced complexity, the average peak signal-to-noise ratio (PSNR) of the proposed algorithm is 0.54 dB higher than that of the previous AM-BTC at a compression ratio of eight.
Published in: IEEE Transactions on Consumer Electronics ( Volume: 62, Issue: 4, November 2016 )
Date of Publication: 02 February 2017
Print ISSN: 0098-3063
INSPEC Accession Number: 16638826
Publisher: IEEE

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Adaptive multi-level block truncation coding for frame memory reduction in LCD overdrive

Adaptive multi-level block truncation coding for frame memory reduction in LCD overdrive

Adaptive multi-level block truncation coding for frame memory reduction in LCD overdrive

Abstract:

To reduce frame memory usage in LCD overdrive, block truncation coding (BTC) is commonly used due to its efficient coding and low implementation cost. However, the inherent limitation of BTC causes severe perceptual artifacts and degrades overdrive performance. To solve this problem, we propose an adaptive multi-level BTC (AM-BTC) in this paper. The AM-BTC firstly overcomes the limitation by adaptively selecting 2-level or 4-level BTC according to the edge property of the coding block. Then, to reduce the bit rate of AM-BTC we improve the 2-level and 4- level BTCs by using only luminance bit-map to represent three color bit-maps. As shown in simulation results, the AM-BTC successfully reduces the frame memory usage to 1/6 and significantly improves coding performance (up to 3.779 dB) as compared with other algorithms. When the AM-BTC is applied to LCD overdrive, it also improves overdrive performance up to 3.390 dB as compared with other competitive methods in literature.
Published in: IEEE Transactions on Consumer Electronics ( Volume: 56, Issue: 2, May 2010 )
Date of Publication: 15 July 2010
Print ISSN: 0098-3063
INSPEC Accession Number: 11414468
Publisher: IEEE
Sponsored by: IEEE Consumer Electronics Society


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