A fuzzy logic approach for the fast approximate computation of image transforms from block JPEG DCT coefficients

M. Gordan, S. Meza, Mihaela Cislariu, B. Orza, A. Vlaicu, D. Capatina, I. Stoian
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引用次数: 1

Abstract

Computationally efficient implementation of different image processing and analysis algorithms is crucial in many modern real world applications. Several modern visual analytics applications involve processing large amounts of compressed image/video data on restricted hardware resources, in a numerically efficient manner. In this context, the formulation of some image analysis/processing algorithms in the compressed image/video domain can bring significant benefits in the computational complexity reduction. An important step to image analysis, feature extraction, based on unitary image transforms is addressed in this paper, in a general form. Starting from the fact that in most popular video compression the intraframes are block discrete cosine transform (DCT) encoded, we present and propose a solution to computing any unitary image transform at pixels block level, starting from the DCT coefficients of the block. Since approximate forms of the transforms are often satisfactory, we propose a fuzzy logic system based approach to optimize the computational complexity with minimal loss of image information. The method is exemplified for the case of the Walsh transform, which shows that even the fastest implementation provides (by reconstruction) images of good quality.
从块JPEG DCT系数中快速近似计算图像变换的模糊逻辑方法
计算效率的实现不同的图像处理和分析算法在许多现代现实世界的应用是至关重要的。一些现代视觉分析应用程序涉及在有限的硬件资源上以数字高效的方式处理大量压缩图像/视频数据。在这种情况下,在压缩图像/视频领域制定一些图像分析/处理算法可以在降低计算复杂度方面带来显著的好处。本文以一般形式讨论了基于酉变换的图像分析的一个重要步骤——特征提取。从大多数流行的视频压缩中帧内都是块离散余弦变换(DCT)编码的事实出发,我们提出并提出了一种从块的DCT系数开始计算像素块级任意幺正图像变换的解决方案。由于变换的近似形式通常是令人满意的,我们提出了一种基于模糊逻辑系统的方法,以最小化图像信息损失来优化计算复杂度。该方法以Walsh变换为例,表明即使是最快的实现(通过重建)也能提供高质量的图像。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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