DocumentCode :
1822700
Title :
Quantization of color image using generic roughness measure
Author :
Sathya, V. ; Niraimathy, P. ; Bagan, K. Bhoopathy
Author_Institution :
Electron. Dept., Madras Inst. of Technol., Chennai, India
fYear :
2015
fDate :
26-28 March 2015
Firstpage :
1
Lastpage :
5
Abstract :
Color quantization is a technique which is used to compress the color space of an image to reduce the visual distortion. The computational complexity of preclustering based quantization is less, but not guaranteed the quantization precision. The quantization quality is high in post clustering based quantization but computational complexity is high. In color quantization the balancing of quantization quality and complexity is very challenging thing. To compensate this, two stage quantization framework is proposed. In first stage, the color space with high resolution is compressed into a color space with condensed type by thresholding. For that, we propose generic roughness measure for effective segmentation of color image. In second stage, the compression results are clustered to form a palette by k-means clustering to get the final results.
Keywords :
image colour analysis; image resolution; image segmentation; quantisation (signal); color image; color quantization; computational complexity; generic roughness measure; image color space; image segmentation; post clustering based quantization; visual distortion; Color; Histograms; Image coding; Image color analysis; Image segmentation; Quantization (signal); Signal processing algorithms; k-means clustering; palette; post clustering; quantization; thresholding;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Signal Processing, Communication and Networking (ICSCN), 2015 3rd International Conference on
Conference_Location :
Chennai
Print_ISBN :
978-1-4673-6822-3
Type :
conf
DOI :
10.1109/ICSCN.2015.7219927
Filename :
7219927
Link To Document :
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