HIGH - QUALITY IMAGE RESTORATION USING LOW - RANK PATCH REGULARIZATION AND GLOBAL STRUCTURE SPARSITY

Image Processing

Today there has been big improvement in digital technology that has led to the development of various usable devices and methods especially in the fields of communications and data transfer to a longer distance. The transmission of data in the form of documents, images and so on is now reachable to all parts of the society and the services are affordable to most of the people. An important aspect is data Compression & restoration and for that matter Image Compression & restoration, as images form a larger part of data being exchanged over the internet through social networking and information sharing apps all over the world. Among different kinds of data, images and videos constitute the bulkiest data. Thus, need for compressing the image files is an important aspect in data communication. The image Compression & restoration is the technique which is applied to compress the pixels of the image to reduce size without compromising image quality. The work contains improvement in vector based Fuzzy DCT algorithm Compression & restoration technique to increase Compression & restoration ratio. In this research work we present a technique for image Compression & restoration, using Fuzzy Discrete Cosine Transform and Fuzzy Logic Techniques. The algorithm used in this project is tested along with several images and the results are compared with other techniques. Our method shows an improved performance both in Compression & restoration ratio as well as image perceptibility. The performance of proposed will be implemented in java. The results shows better PSNR and Compression & restoration ratio as compare to discrete cosine transformation.

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