{"product_id":"9780792383222","title":"Still Image Compression on Parallel Computer Architectures","description":"\u003ch1\u003eStill Image Compression on Parallel Computer Architectures\u003c\/h1\u003e \u003ch2\u003eBevinakoppa, Savitri\u003c\/h2\u003e \u003cp\u003e\u003cem\u003eStill Image Compression on Parallel Computer  Architectures\u003c\/em\u003e investigates the application of parallel-processing  techniques to digital image compression. Digital image compression is  used to reduce the number of bits required to store an image in  computer memory and\/or transmit it over a communication link. Over the  past decade advancements in technology have spawned many applications  of digital imaging, such as photo videotex, desktop publishing,  graphics arts, color facsimile, newspaper wire phototransmission and  medical imaging. For many other contemporary applications, such as  distributed multimedia systems, rapid transmission of images is  necessary. Dollar cost as well as time cost of transmission and  storage tend to be directly proportional to the volume of data.  Therefore, application of digital image compression techniques becomes  necessary to minimize costs. \u003cbr\u003e  A number of digital image compression algorithms have been developed  and standardized. With the success of these algorithms, research  effort is now directed towards improving implementation techniques.  The Joint Photographic Experts Group (JPEG) and Motion Photographic  Experts Group(MPEG) are international organizations which have  developed digital image compression standards. Hardware (VLSI chips)  which implement the JPEG image compression algorithm are available.  Such hardware is specific to image compression only and cannot be used  for other image processing applications. A flexible means of  implementing digital image compression algorithms is still required.  An obvious method of processing different imaging applications on  general purpose hardware platforms is to develop software  implementations. \u003cbr\u003e  JPEG uses an 8 × 8 block of image samples as the basic element  for compression. These blocks are processed sequentially. There is  always the possibility of having similar blocks in a given image. If  similar blocks in an image are located, then repeatedcompression of  these blocks is not necessary. By locating similar blocks in the  image, the speed of compression can be increased and the size of the  compressed image can be reduced. Based on this concept an enhancement  to the JPEG algorithm is proposed, called Bock Comparator Technique  (BCT). \u003cbr\u003e  \u003cem\u003eStill Image Compression on Parallel Computer Architectures\u003c\/em\u003e is  designed for advanced students and practitioners of computer science.  This comprehensive reference provides a foundation for understanding  digital image compression techniques and parallel computer  architectures.\u003c\/p\u003e \u003ch3\u003eDetails\u003c\/h3\u003e \u003cp\u003ePublished by: Springer\u003c\/p\u003e \u003cp\u003ePublication Date: 1998-11-30\u003c\/p\u003e \u003cp\u003eFormat: Hardcover\u003c\/p\u003e \u003cp\u003eISBN-13: 9780792383222\u003c\/p\u003e \u003cp\u003eDOI: 10.1007\/978-1-4615-4967-3\u003c\/p\u003e \u003cp\u003eDimensions: 235.0cm x155.0cm\u003c\/p\u003e \u003cp\u003ePages: 202.0\u003c\/p\u003e ","brand":"Springer US","offers":[{"title":"Default Title","offer_id":45578418520204,"sku":"9780792383222","price":152.99,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0710\/9545\/1788\/files\/9780792383222.jpg?v=1767146623","url":"https:\/\/lateknightbooks.com\/products\/9780792383222","provider":"Late Knight Books and Services, LLC","version":"1.0","type":"link"}