Reduced reference Image Quality Assessment for transmitted images using digital watermarking

Objective Image Quality Assessment (IQA) aims to automatically measure the quality degradation perceived by human eyes. In this paper, a new reduced-reference image quality assessment algorithm for channel distortion (distortion specific metric) has been proposed. This algorithm uses a small part of the original image (as a reduced-reference) and embeds this part, in the image, as a watermark. At the receiver side, this part is extracted from the watermarked distorted image and with the help of received part of the image and the extracted watermark the channel is estimated. In this method, neither receiver requires to know the training sequence in advance nor the sender requires to send the training sequence, and channel can still be estimated using digital watermarking. Once the channel coefficients are estimated, the condition number of the channel convolution matrix gives a direct measure for quality of a received image. Proposed algorithm can simultaneously be used for usual watermarking applications and image quality assessment.

[1]  Yongmin Kim,et al.  A de-blocking algorithm and a blockiness metric for highly compressed images , 2002, IEEE Trans. Circuits Syst. Video Technol..

[2]  Zhou Wang,et al.  Quality-aware images , 2006, IEEE Transactions on Image Processing.

[3]  Paolo Gastaldo,et al.  No-reference quality assessment of JPEG images by using CBP neural networks , 2004, 2004 IEEE International Symposium on Circuits and Systems (IEEE Cat. No.04CH37512).

[4]  H.R. Wu,et al.  A generalized block-edge impairment metric for video coding , 1997, IEEE Signal Processing Letters.

[5]  Shanq-Jang Ruan,et al.  Digital watermarking: Spreading code versus channel coding , 2008, 2008 3rd International Symposium on Communications, Control and Signal Processing.

[6]  Alan C. Bovik,et al.  No-reference quality assessment using natural scene statistics: JPEG2000 , 2005, IEEE Transactions on Image Processing.

[7]  R. Venkatesh Babu,et al.  GAP-RBF Based NR Image Quality Measurement for JPEG Coded Images , 2006, ICVGIP.

[8]  Alan C. Bovik,et al.  The Essential Guide to Image Processing , 2009, J. Electronic Imaging.

[9]  Alan C. Bovik,et al.  Image quality assessment using natural scene statistics , 2004 .

[10]  J. Gotze,et al.  Increased Robustness and Security of Digital Watermarking Using DS-CDMA , 2007, 2007 IEEE International Symposium on Signal Processing and Information Technology.

[11]  Nick G. Kingsbury,et al.  A distortion measure for blocking artifacts in images based on human visual sensitivity , 1995, IEEE Trans. Image Process..