Image Hiding Algorithm in Discrete Cosine Transform Domain Based on Grey Prediction and Grey Relational Analysis

Traditional information hiding algorithms cannot maintain a good balance of capacity,invisibility and robustness.In this paper,a novel blind colour image information hiding algorithm based on grey prediction and grey relational analysis in the Discrete Cosine Transform(DCT) domain is proposed.First,this algorithm compresses the secret image losslessly based on the improved grey prediction GM(1,1)(IGM) model.It then chooses the blocks of rich texture in the cover image as the embedding regions using Double-dimension Grey Relational Analysis(DGRA).Finally,it adaptively embeds the compressed secret bits stream into the DCT domain mid-frequency coefficients,which are decided by those blocks' Double-Dimension Grey Correlation Degree(DGCD) and Human Visual System(HVS).This method can ensure an adequate balance between invisibility,capacity and robustness.Experimental results show that the proposed algorithm is robust against JPEG compression(46.724 6 dB when the compression quality factor is 90%),Gaussian noise(45.531 3 dB when the parameter is(0,0.000 5)) etc.,and it is a blind information hiding algorithm that can be extracted without an original carrier.

DCT based multipurpose watermarking technique for image copyright notification and protection

A multipurpose image watermarking technique based on DCT is proposed to notify and protect the copyright of digital products. In order to achieve this objective, the DCT coefficients of each image block are divided into two parts for embedding the visible and invisible watermarks. The visible watermark is embedded in each DC DCT coefficient and most of the AC DCT coefficients of every block, and the invisible watermark in the rest. Based on the characteristics of Human Visual System (HVS), the embedding strength of the visible watermark is varied in accordance with the underlying content of the host image. The invisible watermark is embedded in a quaternity of midrange frequencies. Experimental results show that the visible watermark is hard to remove and the invisible watermark is robust to common digital signal processing operations.

A NEW IMAGE QUALITY ASSESSMENT BASED ON HVS

This letter proposes a new kind of image quality philosophy—Modulate Quality based on Fixation Points (MQFP) based on Human Visual System (HVS) model. Dissimilar to the former HVS-based quality assessment, the new measure emphasizes particularly on modeling the jumping phenomenon of human sight instead of modeling the visual perception of human. In other words, to model the HVS using fixation points and stay-frequency instead of Contrast Sensitive Function (CSF) etc. which models the visual perception of HVS. The experiment on various frequency-distortion images indicates that the new measure is correlated with the subjective judgment more than the former HVS-based measure and is a robust measure.

Shadow detection combining characters of human vision

A shadow detection method using pulse couple neural network inspired by the characters of human visual system is proposed.More precisely,lateral inhibition of human vision and coefficient of variation are combined together to improve the pulse couple neural network.Shadow detection is considered to be a shadow region segmentation problem.Experiment shows that the presented method is consistent with human vision compared to shadow detection methods based on HSV and pulse couple neural network(PCNN) by both subjective and objective assessments.

Perceptual importance analysis for H.264/AVC bit allocation

The existing H.264/AVC rate control schemes rarely include the perceptual considerations.As a result,the im-provements in visual quality are hardly comparable to those in peak signal-to-noise ratio(PSNR).In this paper,we propose a perceptual importance analysis scheme to accurately abstract the spatial and temporal perceptual characteristics of video contents.Then we perform bit allocation at macroblock(MB)level by adopting a perceptual mode decision scheme,which adaptively updates the Lagrangian multiplier for mode decision according to the perceptual importance of each MB.Simulation results show that the proposed scheme can efficiently reduce bit rates without visual quality degradation.

一种基于DCT系数重组的降参考3D视频质量评价方法

针对3D视频质量评价,提出了一种基于离散余弦变换(DCT)系数重组的降参考质量评价方法。方法主要包括4D数据集构造、DCT变换与重组和降参考(RR)质量评价3个阶段。在4D数据集构造阶段,通过联合视频的空间域、视点域和时间域信息构造包含3D视频全部信息的4D数据集;在DCT变换与重组阶段,首先对数据集进行DCT变换,然后筛选复杂度较高的DCT系数进行重组,得到能够表征3D视频质量的重组系数集;在RR质量评价阶段,首先采用广义高斯分布(GGD)函数对重组后DCT系数集的每个子带进行建模,然后利用系数距离函数和频率比距离函数评估3D视频质量。实验结果表明,本文提出的方法与主观评价结果有较好的相关性,符合人类视觉系统(HVS)。

A network-aware error-resilient method using prioritized intra refresh for wireless video communications

We propose a novel prioritized intra refresh method for the wireless video communication.The proposed method considers the characteristics of the human visual system,the error-sensitivity of the bitstream,and the state of the time-varying wireless channel jointly.An expected perceptual distortion model was used to adjust the intra refresh rate adaptively.This model consists of the perceptual weight map based on an attention model,the bit error probability map based on bitstream size,and the dynamic channel state information(CSI).Experimental results indicate that,compared with other intra refresh methods that consider only the content of the video or the CSI,the proposed method improves the average peak signal-to-noise ratio(PSNR) of the whole frame by about 0.5 dB,and improves the average PSNR of the attention-area by about 0.8 dB.