Context Matching Technique for Prediction Based Lossless Compression Using Rice Coding Technique
D.Eswara Sai
, B.N. Swamy
RGB 2 CFA n CFA 2 RGB Conversion, Prediction based Lossless Compression scheme.
In most digital cameras, pain pill Color Filter Array (CFA) pictures square measure captured and demosaicing is mostly disbursed before compression. Recently, it absolutely was found that compression-first schemes exceed the traditional demosaicing-first schemes in terms of output image quality. underneath this new strategy, digital cameras will have a less complicated style and lower power consumption as computationally significant processes like demosaicing is disbursed in an offline powerful laptop computer. AN economical prediction-based lossless compression theme for pain pill CFA image is planned. It exploits a context matching technique to rank the neighboring constituents once predicting a pixel, AN adaptational color distinction estimation theme to get rid of the color spectral redundancy once handling red and blue samples, and an adaptational Rice secret writing technique for coding the prediction residues. during this compression theme, CFA image is split into two sub-images: an inexperienced sub-image, that contains all inexperienced samples of the CFA image and a non-green sub-image, that holds the red and therefore the blue samples. The inexperienced sub-image is coded 1st and therefore the non-green sub-image follows supported the inexperienced sub-image as a reference. to cut back the spectral redundancy, the non-green sub-image is processed within the color distinction domain whereas the inexperienced sub-image is processed within the intensity domain as a reference for the color distinction content of the non-green sub-image. each sub-image square measure processed information scan sequence with the planned context matching primarily based prediction technique to get rid of the special dependency. The prediction residue planes of the 2 sub-images square measure then entropy encoded consecutively with the planned realization theme of adaptational Rice code. Experimental results show that the planned compression theme will effectively and with efficiency scale back the redundancy in each special and color spectral domains. As compared with the present lossless CFA image secret writing schemes, the planned theme provides the most effective compression performance. In some high-end photography applications, like industrial poster production, original CFA pictures square measure needed for manufacturing prime quality full-color pictures directly. In such cases, lossless compression of CFA pictures is important.
"Context Matching Technique for Prediction Based Lossless Compression Using Rice Coding Technique", IJSDR - International Journal of Scientific Development and Research (www.IJSDR.org), ISSN:2455-2631, Vol.1, Issue 12, page no.104 - 107, December-2016, Available :https://ijsdr.org/papers/IJSDR1612021.pdf
Volume 1
Issue 12,
December-2016
Pages : 104 - 107
Paper Reg. ID: IJSDR_160988
Published Paper Id: IJSDR1612021
Downloads: 000347040
Research Area: Engineering
Country: krishna, andhra pradesh, India
ISSN: 2455-2631 | IMPACT FACTOR: 9.15 Calculated By Google Scholar | ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 9.15 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator
Publisher: IJSDR(IJ Publication) Janvi Wave
