Visually lossless compression for Bayer color filter array using optimized Vector Quantization

详细信息    查看全文

• 作者：M. Lakshmi^a ; ^{lakshmimcfa@gmail.com" class="auth_mail" title="E-mail the corresponding author}Author Vitae ; J. Senthilkumar^b ; ^{jsenthil10@gmail.com" class="auth_mail" title="E-mail the corresponding author}Author Vitae ; Y. Suresh^b ; ^{ysuresh33@gmail.com" class="auth_mail" title="E-mail the corresponding author}Author Vitae
• 关键词：Colour Filter Array (CFA) ; Colour demosaicking ; Bayer pattern ; Image compression ; Vector Quantization (VQ) ; Artificial Bee Colony (ABC) optimization
• 刊名：Applied Soft Computing
• 出版年：2016
• 出版时间：September 2016
• 年：2016
• 卷：46
• 期：Complete
• 页码：1030-1042
• 全文大小：3972 K

文摘

Devices using single sensors to capture colour images are cheaper due to high cost of Charge Couple Device (CCD) sensors or Complementary Metal-Oxide Semiconductor (CMOS) sensors. Single sensor devices use Colour Filter Array (CFA) to sample one colour band at every pixel location. Demosaicking process is applied to interpolate the two missing colours from the surrounding. Typically compression is done on the demosaicked images which may not be efficient due to the individual compression of the different colour space. This work investigated compression of raw data before demosaicking and performs demosaicking to reconstruct the R, G, B bands later. A novel Vector Quantization (VQ) technique for encoding the wavelet decomposed image using Modified Artificial Bee Colony (ABC) optimization algorithm is proposed. The proposed technique is compared with Genetic Algorithm based VQ and ABC based quantization and with standard LBG and Lloyd algorithm. Results show higher Peak Signal-to-Noise Ratio (PSNR) indicating better reconstruction.