基于低复杂度整数近似离散切切夫变换的图像压缩算法的实现

Wang Yuting, L. Xuedong, Hu Zaijun
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引用次数: 1

摘要

离散余弦变换(DCT)在图像压缩领域有着广泛的应用。最近,离散技术变换(DTT)被报道在编码性能上优于DCT。本文首先介绍了数字地面电视。然后介绍了一种求整数近似DTT的方法。采用整数近似DTT对灰度图像进行压缩。由于得到的整数近似DTT矩阵不是正规的,我们需要在它的左边乘以一个对角矩阵。当我们使用整数矩阵进行变换时,对角矩阵必须合并到量化过程中。导出了等效量化矩阵和逆量化矩阵。与JPEG和精确DTT相比,整数近似DTT的重建图像质量略低,但复杂度极低。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Implementation of an Image Compression Algorithm Based on Low Complexity Integer Approximate Discrete Tchebichef Transform
The discrete cosine transform (DCT) is used widely in the area of image compression. Recently, the Discrete Tchebichef Transform (DTT) is reported to be superior to DCT in terms of coding performance. In this paper, DTT is presented first. Then a scheme of deriving the integer approximate DTT is introduced. The integer approximate DTT is used to compress a gray-scale image. Since the resulting integer approximate DTT matrix is not normal, we need to multiply a diagonal matrix to its left. When we use the integer matrix to perform the transform, the diagonal matrix have to be merged into the quantization process. We derive the equivalent quantization matrix and the inverse quantization matrix. Compared with JPEG and exact DTT, the integer approximated DTT shows a bit lower reconstructed image quality but with extreme low complexity.
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