@inproceedings{scholars600,
            note = {cited By 34; Conference of 2009 International Conference on Signal Acquisition and Processing, ICSAP 2009 ; Conference Date: 3 April 2009 Through 5 April 2009; Conference Code:79615},
             doi = {10.1109/ICSAP.2009.39},
            year = {2009},
           title = {Color space selection for color image enhancement applications},
         address = {Kuala Lumpur},
         journal = {2009 International Conference on Signal Acquisition and Processing, ICSAP 2009},
           pages = {208--212},
             url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-77949983934&doi=10.1109\%2fICSAP.2009.39&partnerID=40&md5=b638933d4398ca13eec2d8a3dab3168e},
        keywords = {Color image enhancement; Color representation; Color space; Color space selection; Conversion accuracies; Image contrast enhancement; Multi resolution decomposition; Multi-resolutions; Objective parameters; Perfect reconstruction; Quantitative description; Structural similarity; YUV space, Color image processing; Conversion efficiency; Image enhancement; Signal analysis; Signal processing, Color},
        abstract = {Device independent, quantitative description of color is a challenging problem. Another problem is that even under equal intensity, some colors are visually brighter than others. Different color representations try to overcome these problems, with varying degrees of success. It is for this reason that there are so many standard color representations. In this paper our goal is to analyze and evaluate the various color spaces in color image enhancement applications. Conversion accuracy and structural similarity measure are the two objective parameters to measure the performance of each color space. Eight most common color spaces are formulated and tested. Their conversion efficiency is computed and they are evaluated based on their performance in image enhancement applicability. Image contrast enhancement method based on multi-resolution decomposition is proposed and tested for all the color spaces. The YUV space is has perfect reconstruction while HSI performs the best in the image enhancement. {\^A}{\copyright} 2009 IEEE.},
          author = {Asmare, M. H. and Asirvadam, V. S. and Iznita, L.},
            isbn = {9780769535944}
}