Spatial just noticeable distortion profile for image in DCT domain

In this paper, a DCT based JND model for monochrome pictures is proposed. This model incorporates the spatial contrast sensitivity function (CSF), the luminance adaptation effect and the contrast masking effect based on block classification. Gamma correction is also considered to compensate the original luminance adaptation effect which gives more accurate results. Moreover, a psychophysical experiment was designed to parameterize our model. Experimental results show that the proposed model is consistent with the human visual system. Compared with the other JND profiles, the proposed model can tolerate more distortion and has much better perceptual quality. The proposed JND model can be easily applied in many related areas, such as compression, watermarking, error protection, perceptual distortion metric, and so on.

[1]  Heidi A. Peterson,et al.  Luminance-model-based DCT quantization for color image compression , 1992, Electronic Imaging.

[2]  John F. Canny,et al.  A Computational Approach to Edge Detection , 1986, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[3]  Weisi Lin,et al.  Improved estimation for just-noticeable visual distortion , 2005, Signal Process..

[4]  King Ngi Ngan,et al.  Adaptive cosine transform coding of images in perceptual domain , 1989, IEEE Trans. Acoust. Speech Signal Process..

[5]  Chun-Hsien Chou,et al.  A perceptually optimized 3-D subband codec for video communication over wireless channels , 1996, IEEE Trans. Circuits Syst. Video Technol..

[6]  Weisi Lin,et al.  Motion-compensated residue preprocessing in video coding based on just-noticeable-distortion profile , 2005, IEEE Trans. Circuits Syst. Video Technol..

[7]  Arun N. Netravali,et al.  Digital Pictures: Representation and Compression , 1988 .