• 中国精品科技期刊
  • CCF推荐A类中文期刊
  • 计算领域高质量科技期刊T1类
Advanced Search
Wang Ronggui, Zhang Xinlong, Zhang Xuan, and Fang Shuai. Image Enhancement in the Compressed Domain Based on Retinex Theory[J]. Journal of Computer Research and Development, 2011, 48(2): 259-270.
Citation: Wang Ronggui, Zhang Xinlong, Zhang Xuan, and Fang Shuai. Image Enhancement in the Compressed Domain Based on Retinex Theory[J]. Journal of Computer Research and Development, 2011, 48(2): 259-270.

Image Enhancement in the Compressed Domain Based on Retinex Theory

More Information
  • Published Date: February 14, 2011
  • Existing image enhancement algorithms in the compressed domain can not preserve the details and color information when enhancing the contrast of images. They mostly treat the DCT coefficients uniformly using the same strategy, or can not inhibit artifacts if treating the coefficients differently. A new image enhancement algorithm in the DCT compressed domain based on Retinex theory is proposed. The algorithm divides DCT coefficients into the illumination component (DC coefficients) and the reflection component (AC coefficients) according to Retinex theory. The DC coefficients are adjusted to compress the image dynamic range by mapping the illumination component to an ideal range, using two simple but powerful functions. The AC coefficients which represent reflection component are adjusted to enhance the local details with a new definition of spectral content measure. The fact that perception of image detail information for peopleis based on the ratio of high and low frequency in human visual system leads to the new definition. The block artifacts will be suppressed using a block decomposing strategy with a threshold automatically according to the characteristics of the images to be enhanced. Compared with traditional Retinex and DCT enhancement algorithms, experiment results show the proposed algorithms efficiency in details enhancement and color preserving, also with artifacts compressed.
  • Related Articles

    [1]Gao Guangyong, Ji Chi, Xia Zhihua. Reversible Data Hiding in Color Encrypted Images Based on Color Channels Correlation and Entropy Coding[J]. Journal of Computer Research and Development. DOI: 10.7544/issn1000-1239.202330880
    [2]Guan Xiaoqiang, Wang Wenjian, Pang Jifang, Meng Yinfeng. Space Transformation Based Random Forest Algorithm[J]. Journal of Computer Research and Development, 2021, 58(11): 2485-2499. DOI: 10.7544/issn1000-1239.2021.20200523
    [3]Tian Ye, Xiang Shijun. LBP and Multilayer DCT Based Anti-Spoofing Countermeasure in Face Liveness Detection[J]. Journal of Computer Research and Development, 2018, 55(3): 643-650. DOI: 10.7544/issn1000-1239.2018.20160417
    [4]Liu Shenglan, Feng Lin, Jin Bo, Wu Zhenyu. A New Local Space Alignment Algorithm[J]. Journal of Computer Research and Development, 2013, 50(7): 1426-1434.
    [5]Xiong Gangqiang, Yu Jiande, Xiong Changzhen, Qi Dongxu. Reversible Factorization of U Orthogonal Transform and Image Lossless Coding[J]. Journal of Computer Research and Development, 2012, 49(4): 856-863.
    [6]Zhang Hongyi, Zhang Junying, Zhao Feng. Extraction of Discriminant Features Based on Optimal Transformation and Cluster Centers of Kernel Space[J]. Journal of Computer Research and Development, 2008, 45(12): 2138-2144.
    [7]Chen Yunjie, Zhang Jianwei, Wei Zhihui, Heng Pheng Ann, Xia Deshen. Automatic Chinese Visual Human Image Segmentation in HSV Space[J]. Journal of Computer Research and Development, 2007, 44(12): 2036-2043.
    [8]Wang Huanbao, Zhang Yousheng, and Li Yuan. A Diagram of Strand Spaces for Security Protocols[J]. Journal of Computer Research and Development, 2006, 43(12): 2062-2068.
    [9]Liu Bing, Yan Heping, Duan Jiangjiao, Wang Wei, and Shi Baile. A Bottom-Up Distance-Based Index Tree for Metric Space[J]. Journal of Computer Research and Development, 2006, 43(9): 1651-1657.
    [10]Zhan Yongzhao, Wang Jinfeng, and Mao Qirong. Nested Knowledge Space Model and Awareness Processing in a Collaborative Learning Environment[J]. Journal of Computer Research and Development, 2005, 42(7): 1159-1165.

Catalog

    Article views (957) PDF downloads (761) Cited by()

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return