Test compression / decompression is one of effective methods for testing today's VLSI. In this paper, we discuss test compression with image compression algorithms, e. g., JPEG algorithm. imagecompression algorit...
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(纸本)9780769545837
Test compression / decompression is one of effective methods for testing today's VLSI. In this paper, we discuss test compression with image compression algorithms, e. g., JPEG algorithm. image compression algorithms can not only achieve considerably high compression but also require no additional decompression circuity on a chip under test if the chip includes image decoders. Moreover, we propose a method for generating seeds (or compressed test data) in the case where a JPEG decoder is utilized as a test decompressor. Although JPEG algorithm carries out lossy compression, given a test data, the proposed algorithm can search seeds that can be decompressed to another test data preserving the test quality of the given test data, and produce a small set of seeds with high fault coverage. Experimental results show the proposed method can achieve compression ratio comparable with several previous test compression methods without larger hardware overhead.
We apply principal component analysis (PCA) to the characterization of artifacts in a digital image-acquisition system containing image-compressionalgorithms. The method is successfully applied to web cameras. The cl...
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We apply principal component analysis (PCA) to the characterization of artifacts in a digital image-acquisition system containing image-compressionalgorithms. The method is successfully applied to web cameras. The classification done with the PCA method produces three processes. The pure spatial process retrieves the luminance distribution of a static object. The pure temporal process is directly related with the temporal noise of the system. An intermediate spatial-temporal process reveals the interaction between the compressionalgorithms and the spatial-frequency contents of the object. Without prior information, the PCA method is able to distinguish this interaction from the classical temporal noise. The analysis of the anomalous pixels also reveals the location in the scene where the compressionalgorithms work harder. An extension of this analysis identifies the origin of the anomalous behavior in terms of its spatial or temporal character. (C) 2004 Society of Photo-Optical Instrumentation Engineers.
China has seen an unheard-of surge in interest in deep-learning methods for image restoration in recent years. Most of these strategies draw inspiration from the established variational technique and related optimizat...
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