TY - GEN
T1 - ℘2SNR
T2 - 2012 International Conference on Image Processing, Computer Vision, and Pattern Recognition, IPCV 2012
AU - Moreno, Jaime
PY - 2012
Y1 - 2012
N2 - Estimation of image quality is decisive in the image compression field. This is important in order minimize, induced error via rate allocation[1]. Traditional full-reference algorithms of image quality try to model how Human Visual System detects visual differences and extracts both information and structure of the image. In this work we I propose a quality assessment, which weights the mainstream PSNR by means of a perceptual model (℘ 2SNR). Perceptual image quality is obtained by estimating the rate of energy loss when an image is observed at monotonically increasing distances. Experimental results show that ℘2SNR is the best-performing algorithm, compared with another eight metrics such as MSSIM, SSIM or VIF, among others, when an image is distorted by a wavelet compression. It has been tested across TID2008 image database.
AB - Estimation of image quality is decisive in the image compression field. This is important in order minimize, induced error via rate allocation[1]. Traditional full-reference algorithms of image quality try to model how Human Visual System detects visual differences and extracts both information and structure of the image. In this work we I propose a quality assessment, which weights the mainstream PSNR by means of a perceptual model (℘ 2SNR). Perceptual image quality is obtained by estimating the rate of energy loss when an image is observed at monotonically increasing distances. Experimental results show that ℘2SNR is the best-performing algorithm, compared with another eight metrics such as MSSIM, SSIM or VIF, among others, when an image is distorted by a wavelet compression. It has been tested across TID2008 image database.
KW - Chromatic induction model
KW - Human visual system
KW - Image quality assessment
KW - Wavelet transform
UR - http://www.scopus.com/inward/record.url?scp=84873293087&partnerID=8YFLogxK
M3 - Contribución a la conferencia
AN - SCOPUS:84873293087
SN - 9781601322258
T3 - Proceedings of the 2012 International Conference on Image Processing, Computer Vision, and Pattern Recognition, IPCV 2012
SP - 835
EP - 841
BT - Proceedings of the 2012 International Conference on Image Processing, Computer Vision, and Pattern Recognition, IPCV 2012
Y2 - 16 July 2012 through 19 July 2012
ER -