Just Noticeable Distortion Research Articles

Structural Similarity Quality Metrics in a Coding Context: Exploring the Space of Realistic Distortions

Perceptual image quality metrics have explicitly accounted for human visual system (HVS) sensitivity to subband noise by estimating just noticeable distortion (JND) thresholds. A recently proposed class of quality metrics, known as structural similarity metrics (SSIM), models perception implicitly by taking into account the fact that the HVS is adapted for extracting structural information from images. We evaluate SSIM metrics and compare their performance to traditional approaches in the context of realistic distortions that arise from compression and error concealment in video compression/transmission applications. In order to better explore this space of distortions, we propose models for simulating typical distortions encountered in such applications. We compare specific SSIM implementations both in the image space and the wavelet domain; these include the complex wavelet SSIM (CWSSIM), a translation-insensitive SSIM implementation. We also propose a perceptually weighted multiscale variant of CWSSIM, which introduces a viewing distance dependence and provides a natural way to unify the structural similarity approach with the traditional JND-based perceptual approaches.

Color Image Watermarking Using Multidimensional Fourier Transforms

This paper presents two vector watermarking schemes that are based on the use of complex and quaternion Fourier transforms and demonstrates, for the first time, how to embed watermarks into the frequency domain that is consistent with our human visual system. Watermark casting is performed by estimating the just-noticeable distortion of the images, to ensure watermark invisibility. The first method encodes the chromatic content of a color image into the CIE chromaticity coordinates while the achromatic content is encoded as CIE tristimulus value. Color watermarks (yellow and blue) are embedded in the frequency domain of the chromatic channels by using the spatiochromatic discrete Fourier transform. It first encodes and as complex values, followed by a single discrete Fourier transform. The most interesting characteristic of the scheme is the possibility of performing watermarking in the frequency domain of chromatic components. The second method encodes the components of color images and watermarks are embedded as vectors in the frequency domain of the channels by using the quaternion Fourier transform. Robustness is achieved by embedding a watermark in the coefficient with positive frequency, which spreads it to all color components in the spatial domain and invisibility is satisfied by modifying the coefficient with negative frequency, such that the combined effects of the two are insensitive to human eyes. Experimental results demonstrate that the two proposed algorithms perform better than two existing algorithms - ac- and discrete cosine transform-based schemes.

Information Disguising and Hiding Technique to Protect Digital Elevation Model Data

An information disguising and hiding technique is used to protect DEM (digital elevation model) data for store and transformation in this paper. A method is designed to compress the DEM data with a very low bit ratio which would be hidden in the disguised data. The integer wavelet with parameter is used, and a wavelet coefficients set which can embed the information is built. This paper expands the just noticeable distortion (JND) analysis based on the human visual system (HVS) to apply it in the DEM data. Furthermore this paper constructs Hash one-way by the Rabin method, and the algorithm can protect two groups of the DEM data at a time and be public.

Estimating Just-Noticeable Distortion for Video

Just-noticeable distortion (JND), which refers to the maximum distortion that the human visual system (HVS) cannot perceive, plays an important role in perceptual image and video processing. In comparison with JND estimation for images, estimation of the JND profile for video needs to take into account the temporal HVS properties in addition to the spatial properties. In this paper, we develop a spatio-temporal model estimating JND in the discrete cosine transform domain. The proposed model incorporates the spatio-temporal contrast sensitivity function, the influence of eye movements, luminance adaptation, and contrast masking to be more consistent with human perception. It is capable of yielding JNDs for both still images and video with significant motion. The experiments conducted in this study have demonstrated that the JND values estimated for video sequences with moving objects by the model are in line with the HVS perception. The accurate JND estimation of the video towards the actual visibility bounds can be translated into resource savings (e.g., for bandwidth/storage or computation) and performance improvement in video coding and other visual processing tasks (such as perceptual quality evaluation, visual signal restoration/enhancement, watermarking, authentication, and error protection)

Image watermarking through attack simulation

One of the most significant requirements for a useful watermarking system is strong resistance to a variety of common attacks. Accordingly, the watermark embedding is designed from the attack perspective in this paper. We attempt to develop a new just-noticeable distortion (JND) in the discrete cosine transform (DCT) domain, based on an attack simulation scheme that reversely derives the maximum modification amount embedded in the DCT domain under a condition of imperceptibility. A new location selection approach to watermark embedding is also addressed. We evaluate the fitness of the embedding location by considering the embedding capacity, i.e., the JND of the considered frequency component, in addition to the frequency and the spectral strength, which are usually adopted by the existing methods. Experimental results show satisfactory ability of our method to resist various common attacks such as JPEG compression, smoothing, sharpening, cropping, and noise attacks.

Motion-compensated residue preprocessing in video coding based on just-noticeable-distortion profile

We present a motion-compensated residue signal preprocessing scheme in video coding scheme based on just-noticeable-distortion (JND) profile. Human eyes cannot sense any changes below the JND threshold around a pixel due to their underlying spatial/temporal masking properties. An appropriate (even imperfect) JND model can significantly help to improve the performance of video coding algorithms. From the viewpoint of signal compression, smaller variance of signal results in less objective distortion of the reconstructed signal for a given bit rate. In this paper, a new JND estimator for color video is devised in image-domain with the nonlinear additivity model for masking (NAMM) and is incorporated into a motion-compensated residue signal preprocessor for variance reduction toward coding quality enhancement. As the result, both perceptual quality and objective quality are enhanced in coded video at a given bit rate. A solution of adaptively determining the parameter for the residue preprocessor is also proposed. The devised technique can be applied to any standardized video coding scheme based on motion compensated prediction. It provides an extra design option for quality control, besides quantization, in contrast with most of the existing perceptually adaptive schemes which have so far focused on determination of proper quantization steps. As an example for demonstration, the proposed scheme has been implemented in the MPEG-2 TM5 coder, and achieved an average peak signal-to-noise (PSNR) increment of 0.505 dB over the twenty video sequences which have been tested. The perceptual quality improvement has been confirmed by the subjective viewing tests conducted.

Motion-compensated residue preprocessing in video coding based on just-noticeable-distortion profile

We present a motion-compensated residue signal preprocessing scheme in video coding scheme based on just-noticeable-distortion (JND) profile. Human eyes cannot sense any changes below the JND thres...

Just noticeable distortion model and its applications in video coding

We explore a new perceptually-adaptive video coding (PVC) scheme for hybrid video compression, in order to achieve better perceptual coding quality and operational efficiency. A new just noticeable distortion (JND) estimator for color video is first devised in the image domain. How to efficiently integrate masking effects together is a key issue of JND modelling. We integrate spatial masking factors with the nonlinear additivity model for masking (NAMM). The JND estimator applies to all color components and accounts for the compound impact of luminance masking, texture masking and temporal masking. Extensive subjective viewing confirms that it is capable of determining a more accurate visibility threshold that is close to the actual JND bound in human eyes. Secondly, the image-domain JND profile is incorporated into hybrid video encoding via the JND-adaptive motion estimation and residue filtering process. The scheme works with any prevalent video coding standards and various motion estimation strategies. To demonstrate the effectiveness of the proposed scheme, it has been implemented in the MPEG-2 TM5 coder and demonstrated to achieve average improvement of over 18% in motion estimation efficiency, 0.6 dB in average peak signal-to perceptual-noise ratio (PSPNR) and most remarkably, 0.17 dB in the objective coding quality measure (PSNR) on average. Theoretical explanation is presented for the improvement on the objective coding quality measure. With the JND-based motion estimation and residue filtering process, hybrid video encoding can be more efficient and the use of bits is optimized for visual quality.

Improved estimation for just-noticeable visual distortion

Perceptual visibility threshold estimation, based upon characteristics of the human visual system (HVS), has wide applications in digital image/video processing. An improved scheme for estimating just-noticeable distortion (JND) is proposed in this paper. It is proved to outperform the DCTune model, with the major contributions of a new formula for luminance adaptation adjustment and the incorporation of block classification for contrast masking. The HVS visibility threshold for digital images exhibits an approximately parabolic curve versus gray levels and this has been formulated to yield a more accurate base threshold. Moreover, edge regions have been differentiated via block classification to effectively avoid over-estimation of JND in the said regions. Experiments with different images and the associated subjective tests show improved performance of the proposed scheme over the DCTune model for luminance adaptation (especially in dark regions) and masking effect in edge regions. Our model has further demonstrated to achieve favorable results in perceptual visual distortion gauge and image compression. The improvement in JND estimation facilitates better visual distortion measurement and visual signal compression.

Study on Digital Elevation Mode Data Watermark via Integer Wavelets

In this paper an efficient approach via wavelet for digital watermark in DEM(digital elevation mode) data is developed, which effectly protects the copyright of DEM data and avoids the unauthoritative user. A technique based on lifting scheme is presented to construct the compactly supported wavelets whose coefficients are composed of a free variable. When t=1, the integer wavelets based on lifting scheme only use integral addition and shift, so it's fast and easily realized via hardware. A method is presented to build the wavelet coefficient set which can embed watermark information. The bit is inserted in the high activity texture regions with the maximum strength of Just Noticeable Distortion (JND) tolerance of Human Visual System (HVS). Keeping the terrain figure and hypsography, the digital watermark is robust. A hash one-way is constructed by the Rabin method, and the digital watermark arithmetic can be public.

Image watermarking using tree-based spatial-frequency feature of wavelet transform

In this paper, an image watermarking scheme is developed using the tree-based spatial-frequency feature of wavelet transform. With our approach, the watermark sequence is inserted in those high activity texture regions of an image having the maximum strength of just noticeable distortion (JND) tolerance of the human visual system (HVS). Simulation results show that the proposed method achieves a good compromise between the robustness and transparency.

A new rate control scheme for H.263 video transmission

In some image/video applications, the variable bit rate image/video bitstream will be transmitted over a constant bit rate transmission channel, in which a channel buffer is employed. In this study, a new rate control scheme for H.263 video transmission is proposed. Three proposed techniques include: preprocessing the INTRA coded macroblock (MB) incorporated the just-noticeable-distortion (JND) concept, constructing a bit estimation model in the frequency domain (instead of the bit estimation model in the spatial domain employed in Test Model Near-term version 11 (TMN11)), and adjusting quantization parameter (QP) for each MB by a Lagrangian optimization strategy. In the proposed approach, the target number of bits for a video frame is first obtained by using a simple rate control procedure for the frame layer. The proposed JND preprocessing is applied on all the INTRA coded MBs so that the number of coded bits for a scene changed frame will decrease, without any perceptual loss. Within the MB layer, instead of the bit estimation model in the spatial domain employed in TMN11, a bit estimation model in the frequency domain, directly depending on discrete cosine transform coefficients, is proposed. Then the Lagrange multiplier is used to determine the optimal QP for each MB. The resulting QP and number of coded bits of the current MB are fed backward to update the parameters of the bit estimation model. Based on the simulation results obtained in this study, the proposed approach can meet the target bit rate more accurately, keep a lower channel buffer fullness (delay), and have a larger average frame rate than TMN11, whereas the peak signal-to-noise ratio value and the processing time of the proposed approach are “approximately” as good as that of TMN11.

A perceptually optimized 3-D subband codec for video communication over wireless channels

Visual communication over wireless channels is becoming important in multimedia. Because of the limited bandwidth and high error rates of the wireless channel, the video codec should be designed to have high coding efficiency in maintaining acceptable visual quality at low bit rates and robustness to suppress the distortion due to transmission errors. The coding efficiency of a 3D subband video codec is optimized by removing not only the redundancy due to spatial and temporal correlation but also perceptually insignificant components from video signals. Unequal error protection is applied to the source code bits of different perceptual importance. An error concealment method is employed to hide the distortion due to erroneous transmission of perceptually important signals. The evaluation of each signal's perceptual importance is made first from measuring the just-noticeable distortion (JND) profile as the perceptual redundancy inherent in video signals, and then from allocating JND energy to signals of different subbands according to the sensitivity of human visual responses to spatio-temporal frequencies. Simulation results show that acceptable visual quality can be maintained in transmitting video sequences with low bit rates (<64 kbps) over the wireless channel of high error rates (up to BER=10/sup -2/), and the distortion due to erroneous transmission of coded data can be effectively suppressed. In the simulation, the noisy channel is assumed to be corrupted by the random errors depending on the average strength of the received wave and the burst errors due to Rayleigh fading.

A perceptually tuned subband image coder based on the measure of just-noticeable-distortion profile

To represent an image of high perceptual quality with the lowest possible bit rate, an effective image compression algorithm should not only remove the redundancy due to statistical correlation but also the perceptually insignificant components from image signals. In this paper, a perceptually tuned subband image coding scheme is presented, where a just-noticeable distortion (JND) or minimally noticeable distortion (MND) profile is employed to quantify the perceptual redundancy. The JND profile provides each signal being coded with a visibility threshold of distortion, below which reconstruction errors are rendered imperceptible. Based on a perceptual model that incorporates the threshold sensitivities due to background luminance and texture masking effect, the JND profile is estimated from analyzing local properties of image signals. According to the sensitivity of human visual perception to spatial frequencies, the full-band JND/MND profile is decomposed into component JND/MND profiles of different frequency subbands. With these component profiles, perceptually insignificant signals in each subband can be screened out, and significant signals can be properly encoded to meet the visibility threshold. A new quantitative fidelity measure, termed as peak signal-to-perceptible-noise ratio (PSPNR), is proposed to assess the quality of the compressed image by taking the perceptible part of the distortion into account. Simulation results show that near-transparent image coding can be achieved at less than 0.4 b/pixel. As compared to the ISO-JPEG standard, the proposed algorithm can remove more perceptual redundancy from the original image, and the visual quality of the reconstructed image is much more acceptable at low bit rates.