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Image Halftoning and Inverse Halftoning for Optimized Dot Diffusion
The dot diffusion method for digital halftoning has the advantage of parallelism unlike the error diffusion method. However, image quality offered by error diffusion is still regarded as superior to other known methods. In a recent paper we showed how the dot diffusion method can be improved by opti...
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creator | Mese, Murat Vaidyanathan, P. P |
description | The dot diffusion method for digital halftoning has the advantage of parallelism unlike the error diffusion method. However, image quality offered by error diffusion is still regarded as superior to other known methods. In a recent paper we showed how the dot diffusion method can be improved by optimization of the so called class matrix. In this paper we first review the dot diffusion algorithm and the optimization of the class matrix. A method for inverse halftoning of dot diffused images is then proposed. The method uses wavelet decomposition to eliminate the halftoning noise and does not make use of the knowledge of the class matrix. |
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P ; CALIFORNIA INST OF TECH PASADENA DEPT OF ELECTRICAL ENGINEERING</creatorcontrib><description>The dot diffusion method for digital halftoning has the advantage of parallelism unlike the error diffusion method. However, image quality offered by error diffusion is still regarded as superior to other known methods. In a recent paper we showed how the dot diffusion method can be improved by optimization of the so called class matrix. In this paper we first review the dot diffusion algorithm and the optimization of the class matrix. A method for inverse halftoning of dot diffused images is then proposed. 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The method uses wavelet decomposition to eliminate the halftoning noise and does not make use of the knowledge of the class matrix.</description><subject>ALGORITHMS</subject><subject>COMPOSITE IMAGES</subject><subject>Cybernetics</subject><subject>GRAY SCALE</subject><subject>IMAGE PROCESSING</subject><subject>NEURAL NETS</subject><subject>PHOTOGRAPHIC SCALE</subject><subject>PIXELS</subject><fulltext>true</fulltext><rsrctype>report</rsrctype><creationdate>1998</creationdate><recordtype>report</recordtype><sourceid>1RU</sourceid><recordid>eNrjZHD2zE1MT1XwSMxJK8nPy8xLV0jMS1HwzCtLLSpGEU7LL1LwLyjJzM2sSk1RcMkvUXDJTEsrLc7Mz-NhYE1LzClO5YXS3Awybq4hzh66KSWZyfHFJZl5qSXxji6OxiaWZkZmxgSkAU-vLzI</recordid><startdate>1998</startdate><enddate>1998</enddate><creator>Mese, Murat</creator><creator>Vaidyanathan, P. 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subjects | ALGORITHMS COMPOSITE IMAGES Cybernetics GRAY SCALE IMAGE PROCESSING NEURAL NETS PHOTOGRAPHIC SCALE PIXELS |
title | Image Halftoning and Inverse Halftoning for Optimized Dot Diffusion |
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