Correlation based universal image/video coding loss recovery

Coding artifacts are annoying in highly compressed signals. Most of the existing artifact reduction methods are designed for one specific type of artifacts, codecs, and bitrates, which are complex and exclusive for one type of artifact reduction. Since both the compressed image/video and the coding error contain information of the original signal, they are highly correlated. Therefore, we try to recover some lost data based on the correlation between the compressed signal and the coding error, and introduce a novel and universal artifact reduction method. Firstly, according to the spatial correlation among pixels, a pixel-adaptive anisotropic filter is designed to reconstruct the distorted signal. Next, a globally optimal filter is designed to further recover the coding loss. Experimental results demonstrate that within an extensive range of bitrates, the proposed method achieves about 0.8 dB, 0.45 dB, 0.3 dB, and 0.2 dB on average of PSNR improvement for JPEG, MPEG4, H.264/AVC, and HEVC compressed signals, respectively.     

Multi-symbol QIM video watermarking

This paper introduces the theoretical framework allowing for the binary quantization index modulation (QIM) embedding techniques to be extended towards multiple-symbol QIM (m-QIM, where m stands for the number of symbols on which the mark is encoded prior to its embedding). The underlying detection method is optimized with respect to the minimization of the average error probability, under the hypothesis of white, additive Gaussian behavior for the attacks. This way, for prescribed transparency and robustness constraints, the data payload is increased by a factor of log₂m.m-QIM is experimentally validated under the frameworks of the MEDIEVALS French national project and of the SPY ITEA2 European project, related to MPEG-4 AVC robust and semi-fragile watermarking applications, respectively. The experiments are three-folded and consider the data payload–robustness–transparency tradeoff. In the former case, the main benefit is the increase of data payload by a factor of log₂m while keeping fixed robustness (variations lower than 3% of the bit error rate after additive noise, transcoding and Stirmark random bending attacks) and transparency (set to average PSNR=45 dB and 65 dB for SD and HD encoded content, respectively). The experiments consider 1 h of video content. In the semi-fragile watermarking case, the m-QIM main advantage is a relative gain factor of 0.11 of PSNR for fixed robustness (against transcoding), fragility (to content alteration) and the data payload. The experiments consider 1 h 20 min of video content.     

A dual color images watermarking scheme based on the optimized compensation of singular value decomposition

This paper proposes a novel watermarking algorithm based on the improved compensation of SVD for embedding the color image watermark into the color host image. Firstly, the watermark bit is embedded into 4 × 4 block by modifying the second row first column and the third row first column elements of U component after SVD. Then, the embedded block is compensated by the improved optimization operation for obtaining higher PSNR and larger threshold T. The embedded watermark is extracted from various attacked images by using the relation between the modified elements of U component without resorting to the original data. Moreover, the proposed algorithm overcomes the problem of false positive detection. The experimental results show that the proposed algorithm not only guarantees the invisibility and robustness of the watermark, but also has better performance than other methods mentioned in this paper.     

An automatic region-based video sequence codec based on fractal compression

In order to improve the performance of fractal video coding, we explore a novel fractal video sequences codec with automatic region-based functionality. To increase the quality of decoding image, intra frame coding, deblocking loop filter and sub-pixel block matching are applied to the codec. An efficient searching algorithm is used to increase the compression ratio and encoding speed. Automatic region-based fractal video sequences coding reduces coding stream greatly. Experimental results indicate that the proposed algorithm is more robust, and provides much less encoding time and bitrate while maintaining the quality of decompression image than the conventional CPM/NCIM method and other related references. We compare the proposed algorithm with three algorithms in Refs. [24], [25], [26], and the results of all these four algorithms are compared with H.264. The bitrate of the proposed algorithm is decreased by 0.11% and the other algorithms are increased by 4.29%, 6.85% and 11.62%, respectively. The average PSNR degradations of the four algorithms are 0.71 dB, 0.48 dB, 0.48 dB and 0.75 dB. So the bitrate of the proposed algorithm is decreased and the other algorithms are increased. At the meantime the compression time is reduced greatly, about 79.19% on average. The results indicate that, on average, the proposed automatic region-based fractal video sequences coding system can save compression time 48.97% and bitrate 52.02% with some image quality degradation in comparison with H.264, since they are all above 32 dB and the human eyes are insensitive to the differences.     

Ripplet: A new transform for image processing

Efficient representation of images usually leads to improvements in storage efficiency, computational complexity and performance of image processing algorithms. Efficient representation of images can be achieved by transforms. However, conventional transforms such as Fourier transform and wavelet transform suffer from discontinuities such as edges in images. To address this problem, we propose a new transform called ripplet transform. The ripplet transform is a higher dimensional generalization of the curvelet transform, designed to represent images or two-dimensional signals at different scales and different directions. Specifically, the ripplet transform allows arbitrary support c and degree d while the curvelet transform is just a special case of the ripplet transform (Type I) with c = 1 and d = 2. Our experimental results demonstrate that the ripplet transform can provide efficient representation of edges in images. The ripplet transform holds great potential for image processing such as image restoration, image denoising and image compression.     

Blind image watermarking via exploitation of inter-block prediction and visibility threshold in DCT domain

In this paper, the backward-propagation neural network (BPNN) technique and just-noticeable difference (JND) model are incorporated into a block-wise discrete cosine transform (DCT)-based scheme to achieve effective blind image watermarking. To form a block structure in the DCT domain, we partition a host image into non-overlapped blocks of size 8 × 8 and then apply DCT to each block separately. By referring to certain DCT coefficients over a 3 × 3 grid of blocks, the BPNN can offer adequate predictions of designated coefficients inside the central block. The watermarking turns out to be a process of adjusting the relationship between the intended coefficients and their BPNN predictions subject to the JND. Experimental results show that the proposed scheme is able to withstand a variety of image processing attacks. Compared with two other schemes that also utilize inter-block correlations, the proposed one apparently exhibits superior robustness and imperceptibility under the same payload capacity.     

Free-viewpoint depth image based rendering

In 3D TV research, one approach is to employ multiple cameras for creating a 3D multi-view signal with the aim to make interactive free-viewpoint selection possible in 3D TV media. This paper explores a new rendering algorithm that enables to compute a free-viewpoint between two reference views from existing cameras. A unique property is that we perform forward warping for both texture and depth simultaneously. Advantages of our rendering are manyfold. First, resampling artifacts are filled in by inverse warping. Second, disocclusions are processed while omitting warping of edges at high discontinuities. Third, our disocclusion inpainting approach explicitly uses depth information. We obtain an average PSNR gain of 3 dB and 4.5 dB for the ‘Breakdancers’ and ‘Ballet’ sequences, respectively, compared recently published results. Moreover, experiments are performed using compressed video from surrounding cameras. The overall system quality is dominated by rendering quality and not by coding.     

Blind self-authentication of images for robust watermarking using integer wavelet transform

In this letter a new technique for robust watermarking of images is proposed based on second-generation wavelets (lifting-based integer wavelet transform). The scheme along with its robustness has got the capability of blind self-authentication of the watermarked images. The watermarked images show no perpetual degrading and gives peak signal to noise ratio (PSNR) in excess of 40 dB due to the use of integer-to-integer transform. Simulation results show the superior performance of the proposed technique as compared to a similar existing scheme under different attacks such as filtering, compression and rotation. Further, due to two independent process of watermark sequence extraction proposed in this letter, any alteration in the image results into dissimilar sequences, thereby detecting tampering in the image.     

Performance evaluation of the fractional wavelet filter: A low-memory image wavelet transform for multimedia sensor networks

Existing image wavelet transform techniques exceed the computational and memory resources of low-complexity wireless sensor nodes. In order to enable multimedia wireless sensors to use image wavelet transforms techniques to pre-process collected image sensor data, we introduce the fractional wavelet filter. The fractional wavelet filter computes the wavelet transform of a 256 × 256 grayscale image using only 16-bit fixed-point arithmetic on a micro-controller with less than 1.5 kbyte of RAM. We comprehensively evaluate the resource requirements (RAM, computational complexity, computing time) as well as image quality of the fractional wavelet filter. We find that the fractional wavelet transform computed with fixed-point arithmetic gives typically negligible degradations in image quality. We also find that combining the fractional wavelet filter with a customized wavelet-based image coding system achieves image compression competitive to the JPEG2000 standard.     

Media pattern exhibition mechanism via mobile devices

This paper describes a new methodology of pattern exhibition for digital media that can conceal an imperceptible but recognizable watermark on the media captured with mobile devices. From the human perception, the imperceptible watermark of marked media can preserve the fidelity and readability of the image’s content. With the designed, window-based histogram operation, the embedded pattern of the marked media can be exhibited and recognized visually. That is, the designed mechanism can satisfy the essentials of both visible and invisible watermarking techniques to promote significant pattern sharing and identification for mobile applications. Simulations demonstrate that the peak signal-to-noise ratio (PSNR) of the marked image is superior (around 50–70 dB) to many of the existing watermarking algorithms. The process is of low computational complexity, efficient and can be applied in the real world via mobile devices via inner histogram operation.     

Chaos-based color image block encryption scheme using S-box

A chaos-based color image encryption scheme using bijection is designed. The whole image is diffused by exclusive or (XOR) operation for random rounds, each color component is separated into blocks with the same size. A bijective function f: B → S between block set B and S-box set S, is built. The corresponding 8 × 8 S-box is dynamically generated by the Chen system with variable conditions. The ciphered image can be obtained after substituting each block with the paired S-box. Numerical simulation and security analysis demonstrate that the scheme is practical in image encryption.     

A 24-dB Ku-band low-power linearized 90-nm amplifier with a built-in output buffer

In this paper, we present a 90-nm high gain (24 dB) linearized CMOS amplifier suitable for applications requiring high degree of port isolation in the K_u-band (13.2–15.4 GHz). The two-stage design is composed of a low-noise common-gate stage and a gain-boosting cascode block with an integrated output buffer for measurement. Optimization of input stage and load-port buffer parameters improves the front-end's linear coverage, port return-loss, and overall gain without burdening its power demand and noise contribution. With low gate bias voltages (0.65–1.2 V) and an active current source, <?10 dB port reflection loss and 3.25–3.41 dB NF are achieved over the bandwidth. The input reflection loss of the overall amplifier lies between ?35 and ?10 dB and the circuit demonstrates a peak forward gain of 24 dB at 14.2 GHz. The output buffer improves the amplifier's forward gain by ～9 dB and pushes down the minimum output return loss to ?22.5 dB while raising the front-end NF by only 0.05 dB. The effect of layout parasites is considered in detail in the 90-nm process models for accurate RF analysis. Monte Carlo simulation predicts 9% and 8% variation in gain and noise figures resulting from a 10% mismatch in process. The K_u-band amplifier including the buffer block consumes 7.69 mA from a 1.2-V supply. The proposed circuit techniques achieve superior small signal gain, GHz-per-milliwatt, and range of linearity when compared with simulated results of reported microwave amplifiers.     

No-reference analysis of decoded MPEG images for PSNR estimation and post-processing

We propose no-reference analysis and processing of DCT (Discrete Cosine Transform) coded images based on estimation of selected MPEG parameters from the decoded video. The goal is to assess MPEG video quality and perform post-processing without access to neither the original stream nor the code stream. Solutions are presented for MPEG-2 video. A method to estimate the quantization parameters of DCT coded images and MPEG I-frames at the macro-block level is presented. The results of this analysis is used for deblocking and deringing artifact reduction and no-reference PSNR estimation without code stream access. An adaptive deringing method using texture classification is presented. On the test set, the quantization parameters in MPEG-2 I-frames are estimated with an overall accuracy of 99.9% and the PSNR is estimated with an overall average error of 0.3 dB. The deringing and deblocking algorithms yield improvements of 0.3 dB on the MPEG-2 decoded test sequences.     

An augmented Lagrangian approach to general dictionary learning for image denoising

This paper presents an augmented Lagrangian (AL) based method for designing of overcomplete dictionaries for sparse representation with general l_q-data fidelity term (q ? 2). In the proposed method, the dictionary is updated via a simple gradient descent method after each inner minimization step of the AL scheme. Besides, a modified Iterated Shrinkage/Thresholding Algorithm is employed to accelerate the sparse coding stage of the algorithm. We reveal that the dictionary update strategy of the proposed method is different from most of existing methods because the learned dictionaries become more and more complex regularly. An advantage of the iterated refinement methodology is that it makes the method less dependent on the initial dictionary. Experimental results on real image for Gaussian noise removal (q = 2) and impulse noise removal (q = 1) consistently demonstrate that the proposed approach can efficiently remove the noise while maintaining high image quality.     

A low power dissipation high-speed CMOS image sensor with column-parallel sigma–delta ADCs

A 60frames/s CMOS image sensor with column-parallel inverter-based sigma–delta (ΣΔ) ADCs is proposed in this paper. In order to improve the robustness of the inverter, instead of constant power supply, two buffers are designed to provide power supply for inverters. Instead of using of an operational amplifier, an inverter-based switch-capacitor (SC) circuit is adopted to low-voltage low-power ΣΔ modulator. Detailed analysis and design optimization are provided. Due to the use of the inverter-based ΣΔ ADCs, the conversion speed is improved while reducing the area and power consumption. The proposed CMOS image sensor has been fabricated with 0.18 μm CMOS process. The measurement results show that the random noise (RN) is 7e_rms⁻, the pixel conversion gain is 100 μV/e⁻. Since the measured full well capacity of the pixel is 25000e⁻, the CMOS image sensor achieves a 71 dB dynamic range (DR). The total power consumption at 60frame/s is 58.2 mW.     

Two-layered structure for optimally essential secret image sharing scheme

This paper presents a two-layered structure for optimally sharing a secret image among s essential and n − s non-essential shared shadows using the (t, s, k, n) essential thresholds, that t essential shared shadows and totally k shared shadows are needed to recover the secret image. The presented two-layered structure includes one user-defined parameter m to determine different kinds of optimal results. m = 1 leads to minimum size of total shared shadows (ST) and size of an essential shared shadow is close to size of a non-essential shared shadow. On the other hand, m = t leads to size of an essential shared shadow being twice of size of a non-essential shared shadow to signify the importance of an essential shared shadow. Moreover, the proposed structure overcomes the threshold fulfillment problem in Chen’s scheme (Chen, 2016). Theoretical analyses and experimental results show that the proposed scheme exhibits secure with optimal sharing ratios among related works.     

STI-to-gate distance effects on flicker noise characteristics in 0.13 μm CMOS

The geometry effect on the flicker noise characteristics and the variations in 0.13 μm CMOS transistors were studied. By symmetrically extending the distance between the shallow-trench-isolation (STI) to the gate, both NMOS and PMOS presented obvious improvement on the noise characteristics. As the distance increased from 0.6 μm to 10 μm, the average noise level reduced by more than one order of magnitude (NMOS) and the standard deviations σ_dB improved from 5.95 dB to 1.79 dB for NMOS and from 3.93 dB to 2.17 dB for PMOS, respectively. To further identify the noise mechanism, the devices with asymmetrical STI-to-gate distances were also investigated. It was found that the distance in the source side (SA) has a much higher impact on the observed noise characteristics. The results suggested that the noise characteristics were dominated by the STI stress induced traps for both NMOS and PMOS studied here. In addition, the carrier number fluctuation model with the correlated mobility scattering could be more suitable to describe the noise characteristics in these devices.     

Dictionary learning based reconstruction for distributed compressed video sensing

Distributed compressed video sensing (DCVS) is a framework that integrates both compressed sensing and distributed video coding characteristics to achieve a low-complexity video coding. However, how to design an efficient reconstruction by leveraging more realistic signal models that go beyond simple sparsity is still an open challenge. In this paper, we propose a novel “undersampled” correlation noise model to describe compressively sampled video signals, and present a maximum-likelihood dictionary learning based reconstruction algorithm for DCVS, in which both the correlation and sparsity constraints are included in a new probabilistic model. Moreover, the signal recovery in our algorithm is performed during the process of dictionary learning, instead of being employed as an independent task. Experimental results show that our proposal compares favorably with other existing methods, with 0.1–3.5 dB improvements in the average PSNR, and a 2–9 dB gain for non-key frames when key frames are subsampled at an increased rate.     

Motion Compensated Three-Dimensional Frequency Selective Extrapolation for improved error concealment in video communication

During transmission of video data over error-prone channels the risk of getting severe image distortions due to transmission errors is ubiquitous. To deal with image distortions at decoder side, error concealment is applied. This article presents Motion Compensated Three-Dimensional Frequency Selective Extrapolation, a novel spatio-temporal error concealment algorithm. The algorithm uses fractional-pel motion estimation and compensation as initial step, being followed by the generation of a model of the distorted signal. The model generation is conducted by an enhanced version of Three-Dimensional Frequency Selective Extrapolation, an existing error concealment algorithm. Compared to this existent algorithm, the proposed one yields an improvement in concealment quality of up to 1.64 dB PSNR. Altogether, the incorporation of motion compensation and the improved model generation extends the already high extrapolation quality of the underlying Frequency Selective Extrapolation, resulting in a gain of more than 3 dB compared to other well-known error concealment algorithms.