{"title":"A Survey on Lossless Compression of Bayer Color Filter Array Images","authors":"Alina Trifan, Ant\u00f3nio J. R. Neves","volume":112,"journal":"International Journal of Computer and Information Engineering","pagesStart":729,"pagesEnd":735,"ISSN":"1307-6892","URL":"https:\/\/publications.waset.org\/pdf\/10004205","abstract":"Although most digital cameras acquire images in a raw<br \/>\r\nformat, based on a Color Filter Array that arranges RGB color<br \/>\r\nfilters on a square grid of photosensors, most image compression<br \/>\r\ntechniques do not use the raw data; instead, they use the rgb result<br \/>\r\nof an interpolation algorithm of the raw data. This approach is<br \/>\r\ninefficient and by performing a lossless compression of the raw data,<br \/>\r\nfollowed by pixel interpolation, digital cameras could be more power<br \/>\r\nefficient and provide images with increased resolution given that the<br \/>\r\ninterpolation step could be shifted to an external processing unit. In<br \/>\r\nthis paper, we conduct a survey on the use of lossless compression<br \/>\r\nalgorithms with raw Bayer images. Moreover, in order to reduce the<br \/>\r\neffect of the transition between colors that increase the entropy of<br \/>\r\nthe raw Bayer image, we split the image into three new images<br \/>\r\ncorresponding to each channel (red, green and blue) and we study<br \/>\r\nthe same compression algorithms applied to each one individually.<br \/>\r\nThis simple pre-processing stage allows an improvement of more than<br \/>\r\n15% in predictive based methods.","references":"[1] B. 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