Vector quantization (VQ) is a popular image compression technique with a simple decoding architecture and high compression ratio. Codebook designing is the most essential part in vector quantization. Linde–Buzo–Gray (LBG) is a traditional method of generation of VQ codebook which results in lower PSNR value. A codebook affects the quality of image compression, so the choice of an appropriate codebook is a must. Several optimization techniques have been proposed for global codebook generation to enhance the quality of image compression. In this paper, a novel algorithm called IDE-LBG is proposed which uses improved differential evolution algorithm coupled with LBG for generating optimum VQ codebooks. The proposed IDE works better than the traditional DE with modifications in the scaling factor and the boundary control mechanism. The IDE generates better solutions by efficient exploration and exploitation of the search space. Then the best optimal solution obtained by the IDE is provided as the initial codebook for the LBG. This approach produces an efficient codebook with less computational time and the consequences include excellent PSNR values and superior quality reconstructed images. It is observed that the proposed IDE-LBG find better VQ Codebooks as compared to IPSO-LBG, BA-LBG and FA-LBG.

中文翻译：

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使用改进的差分进化算法进行矢量量化进行图像压缩

矢量量化 (VQ) 是一种流行的图像压缩技术，具有简单的解码架构和高压缩比。码本设计是矢量量化中最重要的部分。Linde–Buzo–Gray (LBG) 是一种传统的 VQ 码本生成方法，导致较低的 PSNR 值。码本影响图像压缩的质量，因此必须选择合适的码本。已经提出了几种用于全局码本生成的优化技术，以提高图像压缩的质量。在本文中，提出了一种称为 IDE-LBG 的新算法，该算法使用改进的差分进化算法与 LBG 相结合来生成最佳 VQ 码本。建议的 IDE 比传统的 DE 工作得更好，修改了缩放因子和边界控制机制。IDE 通过有效探索和利用搜索空间来生成更好的解决方案。然后将IDE得到的最优解作为LBG的初始码本提供。这种方法以更少的计算时间产生高效的码本，其结果包括出色的 PSNR 值和优质的重建图像。据观察，与 IPSO-LBG、BA-LBG 和 FA-LBG 相比，所提出的 IDE-LBG 找到了更好的 VQ 码本。