Paper
10 December 1986 Low-Rate Entropy Coding Of Transformed Images
Sharaf E. Elnahas, Kou-Hu Tzou
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Abstract
TWo entropy coding schemes are investigated in this paper by estimating the entropies that specify the lower bounds of their coding rates. In the firSt scheme, we use a traditional combination of runlength and Huffman codes. Arithmetic codes are used in the second scheme. The results indicate that binary arithmetic codes outperform runlength codes by a factor of 34 % for low-rate coding of the zero-valued coefficients of the cosine transform of digital images. Hexadecimal truncated arithmetic codes provided a coding rate improvement as high as 28 % over truncated Huffman codes at low rates. The complexity of these arithmetic codes is suitable for practical implementation.
© (1986) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Sharaf E. Elnahas and Kou-Hu Tzou "Low-Rate Entropy Coding Of Transformed Images", Proc. SPIE 0697, Applications of Digital Image Processing IX, (10 December 1986); https://doi.org/10.1117/12.976200
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Cited by 10 scholarly publications.
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KEYWORDS
Binary data

Image compression

Signal to noise ratio

Chemical elements

Digital image processing

Distortion

Evolutionary algorithms

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