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Image JND threshold value computing method in DCT domain and based on visual attention mechanism

A visual attention, image technology, applied in the direction of image communication, television, electrical components, etc., can solve problems such as no consideration, and achieve the effect of fine and accurate segmentation

Inactive Publication Date: 2013-12-25
TONGJI UNIV
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Problems solved by technology

Since most image / video coding standards are based on the DCT domain (such as JPEG, H.261 / 3 / 4, MPEG-1 / 2 / 4), the JND model based on the DCT domain has attracted the attention of many researchers, such as Document 2 (see Z.Wei and K.N.Ngan, "Spatial just noticeable distortion profile for image in DCT domain," In Proc.IEEE Int.Conf.Multimeda and Expo, pp.925-928, 2008.) combines the brightness of the image Adaptive characteristics, spatial contrast effect and contrast masking effect based on block classification, but this model does not consider the impact of the human eye's visual attention mechanism on the JND model, so the calculation accuracy needs to be further improved

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  • Image JND threshold value computing method in DCT domain and based on visual attention mechanism
  • Image JND threshold value computing method in DCT domain and based on visual attention mechanism
  • Image JND threshold value computing method in DCT domain and based on visual attention mechanism

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[0030] Below in conjunction with accompanying drawing, the present invention will be further described with specific example:

[0031] The example that the present invention provides adopts MATLAB7 as the emulation experiment platform, uses the bmp grayscale image Airplane of 512 * 512 as the selected test image, describes this example in detail below in conjunction with each step:

[0032] Step (1), select the bmp grayscale image of 512 * 512 as the image of input test, carry out the DCT transformation of 8 * 8 to it, transform it into DCT domain by space domain;

[0033] In step (2), in the DCT domain, the perceivable distortion JND value is obtained by calculating the product of the basic threshold value of the spatial contrast and the adaptive modulation factor of the brightness, and the calculation formula is as follows:

[0034] T JND (n, i, j) = T Basic (n, i, j) × F lum (n) (1)

[0035] Among them, T Basic (n, i, j) represents the spatial contrast sensitivity thre...

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Abstract

The invention provides an image JND threshold value computing method in a DCT domain and based on a visual attention mechanism. The image JND threshold value computing method comprises two schemes combining significance and block classification, wherein one scheme includes that a visual attention masking factor of a single point is combined with block classification masking factors according to a point-to-point mode; the other scheme includes that the average significance of all blocks represents significance of the whole block classification, and then a visual attention masking factor of each block is combined with block classification masking factors according to a block-to-block mode. A value obtained through calculation by a comprehensive contrast masking function is utilized to modulate a traditional JND threshold value, and finally a more accurate JND threshold value is obtained. The two schemes of the method can both effectively improve accuracy of the JND threshold value, and therefore the JND threshold value is matched with a human eye vision system. A model achieved by the image JND threshold value computing method can contain more noise, and in the aspect of the PSNR, the model can be improved by 0.54DB on average.

Description

technical field [0001] The invention relates to the technical field of image / video coding. technical background [0002] Traditional image / video coding technology mainly compresses and codes spatial redundancy, time domain redundancy, and statistical redundancy, but rarely considers the characteristics and psychological effects of the human visual system, so a large amount of visual redundant data is encoded and transmitted , in order to further improve the efficiency of coding, researchers have started research on removing visual redundancy. At present, an effective method to represent visual redundancy is the least detectable distortion model based on psychology and physiology, referred to as the JND model, which can also be called the just detectable distortion model, that is, the changes that the human eye cannot perceive, due to various human eyes. The shielding effect means that the human eye can only perceive noise above a certain threshold, which is the just detecta...

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Application Information

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IPC IPC(8): H04N7/26H04N7/30H04N17/00
Inventor 张冬冬高利晶臧笛孙杳如
Owner TONGJI UNIV
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