Verification of role of data scanning direction in image compression using fuzzy composition operations

A digital image is a numerical representation of visual perception that can be manipulated according to specifications. In order reduce the cost storage and transmission, images are compressed. Depending upon quality reconstruction, compression methods categorized as Lossy Lossless compression. The lossless techniques, where exact recovery data possible, most challenging task considering tradeoff between ratio achieved reconstruction. inherent redundancies like interpixel redundancy coding in exploited for this purpose. treated by decorrelation using Run-length Encoding, Predictive Coding, other Transformation Coding techniques. While entropy-based Huffman codes, arithmetic LZW algorithm, which eliminates redundancy. During implementation these sequential algorithms, direction used scanning plays an important role. study various techniques schemes presented paper. experimentation on 100 gray-level comprising 10 different classes carried out understand effect its compressibility. interrelation maximum length Run similarly resultant number Tuples reported. Considering fuzzy nature relations, composition operations max-min, min-max, max-mean compositions decision-making. way, rational comment suitable particular class made conclusion.