After introducing this compression method, it is applied on different images from Corel dataset for experimental results and analysis. This method is consists of a new transformation method called Enhanced DPCM Transformation (EDT) which has a good energy compaction and a suitable Huffman encoding. In this dissertation, we use differential pulse code modulation for image compression lossless and near-lossless compression method is introduced which is efficient due to its high compression ratio and simplicity. In real time application which needs hardware implementation, low complex algorithm accelerates compression process. Lossless compressions are JPEG, JPEG-LS and JPEG 2000 is few well-known methods for lossless compression. Regard to importance of images information, lossless or lossy compression is preferred. Compression of images is used in some applications such as profiling data and transmission systems. Images include information about human body which is used for different purposes such as medical, security and other plans. An itemized overview on many existing DC strategies is expressed to address the present necessities in lieu of the information quality, coding plans and applications in request to break down how DC strategies and its applications have advanced a similar investigation is performed to recognize the commitment of inspected procedures as far as their qualities, fundamental ideas, exploratory variables and constraints. As DC ideas result to viable usage of accessible storage space and effective transfer speed, various methodologies were created in a few angles. The major challenge that systems face today is the size of data thereby the vision of these systems is to compress the data to its maximum so that the storage space, processing time is reduced thereby making the system effective. There is a direct proportional relationship between the size of data to the efficiency of a given system. The onus lies on the network to compute, process, transfer and store this data. In the digital world today, data is growing tremendously.
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January 2023
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