| 摘要: |
| 目的 为了提高解压缩重建图像的视觉效果和质量。方法 结合人眼视觉特性和图像变换域频谱系数特征， 构建了一个提升解压缩图像质量的补偿矩阵， 用以在解压缩过程中对反量化系数起到补偿作用， 并采用JPEG压缩算法， 对3幅彩色图像进行仿真实验验证。结果 在6种压缩比下， 相对于JPEG技术， 在解压缩重建图像过程中加入补偿矩阵后， 反映提升图像质量的参数SSIM和PSNR值分别平均增加了2.5275%和11.8977%。结论 该补偿矩阵有效提升了解压缩图像的质量， 较好地弥补了压缩过程中因量化而导致图像质量下降的不足。 |
| 关键词: 图像压缩 人眼视觉特性 补偿矩阵 结构相似度 |
| DOI： |
| 分类号:TS865 |
| 基金项目:国家自然科学基金 （61301237）；陕西省科技新星计划 （2015KJXX-42）；陕西省教育厅专项科研基金 （2015JK1139） |
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| A Novel Method to Improve Quality of Decompressed Image Based on Characteristics of Human Visual System |
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YAO Jun-cai, SHEN Jing
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Shaanxi University of Technology， Hanzhong 723000， China
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| Abstract: |
| This study aimed to improve the visual effect and the quality of the reconstructed images. Combining the characteristics of human visual system and spectrum coefficients in the transformation domain, a compensation matrix was constructed to improve the quality of decompressed image, which was to compensate the inverse quantization coefficients during the decompression. And the simulation experiments were carried out for three color images based on JPEG compression algorithm. The experimental results showed that, under the six compression ratios, compared with JPEG technology, SSIM and PSNR average values that reflected improved image quality were increased respectively by 2.5275% and 11.8977% by adding the compensation matrix in the reconstruction process of the decompressed image. The experiment showed the compensation matrix can enhance effectively the quality of the decompressed image, and compensates the quality degradation due to quantization during compression. |
| Key words: image compression characteristics of human visual system compensation matrix structural similarity |
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