Improved Image Sequence Compression Efficiency Through Various Techniques

With the development of innovation and door into the Digital Age, the world has ended up in the midst of an incomprehensible measure of data. To take advantage of correspondence channels and capacity frameworks, it is important to augment their proficiency by minimizing the transmission and capacity of repetitive, or pointless, data. By and large the images are as sequences which are greatly connected. These images are vital and subsequently lossless image compression is expected to recreate the first nature of the image with no loss of data. Lossless compression system is obliged to lessen the quantity of bits to store these image sequences and take less time to transmit over the system. To endeavor the relationship of the image sequences and to meet the test of image compression, some new methods have been proposed. The proposed methods are SDH (Super-Spatial Structure Prediction, Diamond Search algorithm, Head Code Compression), SBL (Super-Spatial Structure Prediction, Binary Tree Search algorithm, LZ8), SIB (Super-Spatial Structure Prediction, Inverse Diamond Search algorithm, Bose, Chaudhuri and Hocquenghem) which intensifies the compression ratio with no loss of information. Results are thought about as far as Compression Ratio, Peak Signal-to-Noise Ratio and Bits per pixel to the earlier expressions. Test consequences of our proposed methods for image sequences accomplish preferred diminishment over the other cutting edge lossless image compression methods.