2015Unpublished venueRequires access

Lossless Image Compression Using Differential Pulse Code Modulation and its Application

Rime Raj Singh Tomar, Kapil Jain

Open publisher page 10 citations

Abstract

Images include information about human body which is used for different purposes such as medical, security and other plans. Compression of images is used in some applications such as profiling data and transmission systems. Regard to importance of images information, lossless or lossy compression is preferred. Lossless compressions are JPEG, JPEG-LS and JPEG 2000 is few well-known methods for lossless compression. In real time application which needs hardware implementation, low complex algorithm accelerates compression process. 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. 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. After introducing this compression method, it is applied on different images from Corel dataset for experimental results and analysis. Also we compare it with other existing methods with respect to parameter compression ratio, peak signal noise ratio and mean square error.

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What this paper is about

Images include information about human body which is used for different purposes such as medical, security and other plans. Compression of images is used in some applications such as profiling data and transmission systems. Regard to importance of images information, lossless or lossy compression is preferred. Lossless compressions are JPEG, JPEG-LS and JPEG 2000 is few well-known methods for lossless compression. In real time application which needs hardware implementation, low complex algorithm accelerates compression process. 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. 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. After introducing this compression method, it is applied on different images from Corel dataset for experimental results and analysis. Also we compare it with other existing methods with respect to parameter compression ratio, peak signal noise ratio and mean square error.

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Available abstract

Images include information about human body which is used for different purposes such as medical, security and other plans. Compression of images is used in some applications such as profiling data and transmission systems. Regard to importance of images information, lossless or lossy compression is preferred. Lossless compressions are JPEG, JPEG-LS and JPEG 2000 is few well-known methods for lossless compression. In real time application which needs hardware implementation, low complex algorithm accelerates compression process. 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. 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. After introducing this compression method, it is applied on different images from Corel dataset for experimental results and analysis. Also we compare it with other existing methods with respect to parameter compression ratio, peak signal noise ratio and mean square error.

Key concepts: Lossy compression, Lossless compression, Lossless JPEG, Computer science, Image compression, Data compression, Huffman coding, JPEG

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