nils-herrmann/clean_scirepeval huggingface dataset:
Automatic white balancing using standard deviation of RGB components

A good automatic white balancing algorithm is an essential image pre-processing component in consumer digital still cameras, and it can greatly improve the final image quality. In this paper, an automatic white balancing algorithm based on the standard deviation of RGB components of the pre-captured image is proposed. A light source model for evaluation of an automatic white balancing is also described. The simulation results show that the proposed algorithm can improve the final image quality of the captured image.
A novel approach to fast multi-frame selection for H.264 video coding

The latest under development video coding standard, H.264, uses multiple reference frames to improve the rate-distortion performance. However, the motion estimation process involved is computational intensive and increases linearly with the number of allowed reference frames. In this paper, a novel fast multi-frame selection method (FMFME) is proposed for H.264 video coding. The proposed FMFME can efficiently reduce the computational cost up to 76% with similar quality and bit-rate.
Parameter estimation for image/video transcoding

In most of the current image/video compression standard, such as JPEG, MPEG, H.263, etc, the DCT is used. The DCT coefficients for every AC frequency component usually have Laplacian distribution. Such a distribution is critical in the image or video transcoding system. Therefore, the parameter in the distribution should be well estimated. Different from the normal parameter estimation, in the transcoding system, the original DCT value is unavailable, and only the dequantized value is available. In this paper, we propose 3 estimation methods based on the dequantized value for the transcoding system. The simulation demonstrates that they can yield very good results. In addition, under a fixed bit rate, they can work even better than estimation with the original DCT value in the sense of image/frame's PSNR.
Unidirectional motion compensated temporal interpolation

Common techniques such as frame repetition or linear interpolation for reconstructing skipped frames in temporally subsampled video sequence tend to introduce undesirable artifacts. A previously proposed technique, motion compensated temporal interpolation (MCTI) can interpolate video frames in the time domain with good image quality at the cost of high computational requirement and substantial memory requirement. In this paper, we propose an algorithm called Unidirectional Motion Compensated Temporal Interpolation (UMCTI) which has lower computational and memory requirement but achieves considerably better peak-signal-to-noise ratio (PSNR). Several variants incorporating stationary block detection and/or overlapping motion compensation are also studied.
A novel fast two step sub-pixel motion estimation algorithm in HEVC

Motion estimation (ME) is one of the most time consuming parts in video coding standard. As fast integer-pixel ME algorithm becoming more and more powerful, it is important to develop fast sub-pixel ME algorithm since the computational complexity of sub-pixel ME compared to integer-pixel ME has become relatively significant. In this paper, a novel fast sub-pixel ME algorithm is proposed. This algorithm first approximates the error surface of the sub-pixel position by a second order function and predicts the minimum point by minimizing the function at half-pixel accuracy. Then another second order approximation within a smaller area which is determined by the previous step is modeled to predict the best sub-pixel position. Experimental results show that the proposed method can reduce the sub-pixel search points significantly with negligible quality degradation.
Fast motion vector re-estimation for arbitrary video downsizing using spatial-variant filter

To downsize a compressed video to a lower resolution, the straightforward method is to decompress the compressed video, downsample the video in spatial domain and then re-compress the downsampled video. This process can be computationally expensive unless fast motion vector re-estimation methods are used. In this paper, the use of a spatial-variant filter (SVF) as a fast motion vector re-estimation method for arbitrary downsizing factor is investigated. Simulation results suggest that the SVF can improve the quality of the existing fast algorithms in terms of PSNR. With a little bit of local search, its PSNR can be close to the full search
Intra prediction with adaptive CU processing order in HEVC

The High Efficiency Video Coding (HEVC) utilizes Z-scan order to process coding units (CUs). For intra prediction, this order cannot fully exploit the spatial correlation between adjacent CUs. After transform and quantization, the residue still contains lots of energy along edges which consumes many bits for compression. To effectively reduce the residue energy along edges, a novel intra prediction approach is proposed, where the CU processing order is changed adaptively. Two additional orders are introduced in this paper besides traditional Z-scan order. Up to 1.9% bit saving is achieved in our experiments on HEVC test model. We also propose two fast order selection algorithms and the observed gains are obtained with 27% and 2% encoding time increase compared to HEVC, respectively.
A novel self conjugate halftone image watermarking technique

In this paper, we propose a novel way called Data Hiding Self Conjugate Error Diffusion to hide invisible patterns in a single error diffused halftone image. The hidden patterns would appear on the halftone image when the halftone image is folded or overlaps with its own rotated version. Simulation results show that the halftone images have good visual quality and the hidden pattern is visible clearly.
3D motion in visual saliency modeling

Visual saliency is a probabilistic estimate of how likely a given spatial area in an image or video is to attract human visual attention relative to other areas. Bottom-up saliency models aggregate low-level image features like luminance and color contrast, flicker, 2D motion, etc. to construct a plausible saliency map. In this paper, we introduce 3D motion (object movements towards or away from the observer) into bottom-up video saliency modeling. Given availability of per-pixel depth maps, we first propose a novel algorithm to estimate 3D motion vectors (3DMVs) for arbitrarily shaped sub-blocks in texture-plus-depth videos. We then derive two feature channels from 3DMVs to be incorporated into a widely accepted bottom-up saliency model. Experiments on subjective quality of Region-of-Interest (ROI) based video coding show that our enriched saliency model with 3DMV channels is more accurate in estimating human visual attention.
Adaptive depth map assisted matting in 3D video

Depth map is widely adopted and available in the 3D research area. Combining the depth map with the matting techniques is helpful to the original matte and depth image based rendering in 3D. Herein, in this paper, a novel adaptive depth map assisted matting approach with concise integration is presented and applied to achieve favorable matting results. In this approach, the Lagrange-multiplier-free closed form solution is firstly derived to reduce the computation complexity and to increase matting accuracy. Based on the work of Levin et al. on closed form matting, an improved alpha matte is then achieved by introducing an adaptive smoothness criterion which is the function of depth map variance. Finally, the matting system is capable of working in a full automatical way by generating the trimap from the depth information. Simulation results demonstrate that the proposed method is able to efficiently generate an alpha matte with an roughly user specified scribbles or an automatically generated trimap.
Novel motion compensation for wavelet video coding using overlapping

The discrete wavelet transform (DWT) has several advantages in multi-resolution analysis and subband decomposition, which has been successfully used in image compression. In this paper, we will extend the usage of DWT to video compression and focus on motion estimation (ME) and motion compensation (MC) in wavelet domain. The ME used in this paper is Low-Band-Shift Motion Estimation (LBSME)  and a novel MC in wavelet domain is proposed. With this novel method, ME/MC in wavelet domain now is comparable with ME/MC in spatial domain and the performance is superior to other ME/MC methods in wavelet domain.
Seamless View Synthesis Through Texture Optimization

In this paper, we present a novel view synthesis method named Visto, which uses a reference input view to generate synthesized views in nearby viewpoints. We formulate the problem as a joint optimization of inter-view texture and depth map similarity, a framework that is significantly different from other traditional approaches. As such, Visto tends to implicitly inherit the image characteristics from the reference view without the explicit use of image priors or texture modeling. Visto assumes that each patch is available in both the synthesized and reference views and thus can be applied to the common area between the two views but not the out-of-region area at the border of the synthesized view. Visto uses a Gauss-Seidel-like iterative approach to minimize the energy function. Simulation results suggest that Visto can generate seamless virtual views and outperform other state-of-the-art methods.
Efficient intra-prediction algorithm in H.264

In the upcoming H.264, intra-prediction with block sizes of 4/spl times/4 and 16x16 is used to compress I-frame. However, there are 9 or 4 candidate modes for the 4x4 or 16x16 intra-prediction. The full search algorithm to choose the modes is computationally expensive. In this paper, we suggest an efficient intra-prediction (EIP) algorithm based on early termination, selective computation of highly probable modes, and partial computation of the cost function. The proposed EIP reduces the complexity considerably while maintaining similar PSNR and bit rate.
Color Demosaicking using Direction Categorization

We propose a novel color demosaicking algorithm using direction categorization. Each pixel is classified as vertical, horizontal or smooth before interpolation. The categorization is based on gradient change within same channel, color differences and neighbors categories, so it explores relationship between intra-and inter-color channels. Color artifacts in reconstructed images are significantly reduced because directions of interpolation across edges are greatly avoided. Experimental results show that our proposed algorithm has high PSNR and the visual quality of reconstructed images is also obviously improved.
Map automatic input based on NN and GAs

With some intelligent algorithms, such as genetic algorithms (GA) and Kohonen neural network (NN), in addition to traditional digital image processing algorithms, a color map automatic input algorithm is proposed in this paper which is important for the data acquisition of CAD and GIS. These have been realized in our Digital Map System (DMS). In this paper, a new color image segmentation algorithm based on color space transformation and vectorization algorithm based on GA are presented in detail.
Maximum a Posterior and Perceptually Motivated Reconstruction Algorithm: A Generic Framework

Most of the existing image reconstruction algorithms are application specific, and have generalization issues due to the need for parameter tuning and an unknown level of signal distortion. Addressing these problems, in this paper, we propose an efficient perceptually motivated and maximum a posterior (MAP)-based generic framework for image reconstruction. This can be applied to several image/video processing applications, where there is a necessity to improve reconstruction accuracy and suppress visible artifacts, such as denoising, deinterlacing, interpolation, de-blocking of Jpeg/Jpeg-2000, and demosaicing. The gradient magnitudes are noise insensitive to a moderate levels of noise and we propose to utilize this property for finding pixels with similar edge semantics in the neighborhood when neighboring pixels are noisy. With this view, we incorporate the gradient magnitude similarity based image quality assessment metric with the MAP estimation and, in turn, it can better approximate the variance of the MAP, as compared to nonlinear filters. The proposed generic algorithm (without manually tuning any parameters) is shown to produce a better quality of reconstruction when compared to the state-of-the-art application-specific algorithms, for most of the image processing applications.
Locally optimal and suboptimal signal detection in transformation noise

The efficacy of the optimal detector of a known vanishingly small signal in additive nonwhite transformation noise is compared with that of some eleven structurally simpler suboptimal detectors. Simulation is done under various signal choices, marginal densities, and correlation functions. The block g/sub lo/ and the block combination g followed by R/sub v//sup -1/ in the optimal detector structure are found to be important for good performance in constant and oscillating signals, respectively. Two suboptimal detectors with these block structures, D/sub 8/ and D/sub 10/, are found to perform well consistently in all situations considered. A structurally simple suboptimal detector D/sub 2/ is found to be good in the cases with less correlated noise.
Rate-Distortion Optimized Transforms Based on the Lloyd-Type Algorithm for Intra Block Coding

The directional intra prediction (IP) in H.264/AVC and HEVC tends to cause the residue to be anisotropic. To transform the IP residue, Mode Dependent Directional Transform (MDDT) based on Karhunen Loève transform (KLT) can achieve better energy compaction than DCT, with one transform assigned to each prediction mode. However, due to the data variation, different residue blocks with the same IP mode may not have the same statistical properties. Instead of constraining one transform for each IP mode, in this paper, we propose a novel rate-distortion optimized transform (RDOT) scheme which allows a set of specially trained transforms to be available to all modes, and each block can choose its preferred transform to minimize the rate-distortion (RD) cost. We define a cost function which is an estimate of the true RD cost and use the Lloyd-type algorithm (a sequence of transform optimization and data reclassification alternately) to find the optimal set of transforms. The proposed RDOT scheme is implemented in HM9.0 software of HEVC. Experimental results suggest that RDOT effectively achieves 1.6% BD-Rate reduction under the Intra Main condition and 1.6% BD-Rate reduction under the Intra High Efficiency (HE) 10bit condition.
Efficient rate control for JPEG2000 image coding

JPEG2000 is the new image coding standard which can provide superior rate-distortion performance over the old JPEG standard. However, the conventional post-compression rate-distortion (PCRD) optimization scheme in JPEG2000 is not efficient. It requires entropy encoding all available data even though a large portion of them will not be included in the final output. In this paper, three rate control methods are proposed to efficiently reduce both the computational complexity and memory usage over the conventional PCRD method. The first method, called successive bit-plane rate allocation (SBRA), allocates the bit rate by using the currently available rate-distortion information only. The second method, called priority scanning rate allocation (PSRA), allocates bits according to certain prioritized ordering. The third method uses PSRA to achieve optimal truncation as PCRD without encoding of all the image details and is called priority scanning with optimal truncation (PSOT). Simulation results suggest that the three proposed methods provide different tradeoff among visual quality, computational complexity, coding delay and working memory size. SBRA is memoryless and causal and requires the least computational complexity, lowest coding delay and achieves good visual quality. PSRA achieves higher PSNR than SBRA at the expense of larger working memory size and longer coding delay. PSOT gives the best PSNR but requires even more computation, delay and memory.
Temporal error concealment for video transmission

In this paper, we propose a temporal error concealment algorithm for video transmission in an error-prone environment. The error concealment algorithm employed an edge detection algorithm and progressive median motion vector concealment. First, the edges are detected and concealed portion by portion. Then, the corrupted MB is partitioned by the reconstructed edges and each partition is concealed by progressive median motion vector individually. The proposed algorithm shows better performance on both objective and subjective quality over the existing temporal error concealment algorithm
Rate distortion optimized transform for intra block coding for HEVC

The Discrete Cosine Transform is statistically optimal for first order Markov signals, which is widely used in image and video coding. However, in the intra frame coding of H.264/AVC, it is known that after directional intra prediction, there is still anisotropic features left in residue signals. And the features are related to the intra prediction modes. In order to represent the corresponding features, mode dependent directional transform (MDDT), which is based on Karhunen Loeve transform (KLT), was derived and adopted into JMKTA software, which is a preliminary software platform for High Efficiency Video Coding (HEVC)[2]. Within the MDDT scheme, each prediction mode has its correspondent transform. However, due to the data variation, this mode dependent classification may not lead to optimal residual data separation. It means that even though the residue blocks are using the same prediction mode, they may exhibit different statistical or structural properties. Sometimes, the mode dependent transform basis functions can not represent the residue signal very well. Therefore, in this paper, we propose a rate distortion optimized transform scheme, which provides a transform selection capability. The proposed scheme is implemented in HM0.9 for HEVC, achieving 3.2% BDBR in Intra Low Complexity (LoCo) condition and 2.0% BDBR in Intra High Efficiency (HE) condition.
Arbitrarily-shaped video coding: smart padding versus MPEG-4 LPE/zero padding

An effective padding scheme, called the smart padding (SmartPad), has been developed recently for the DCT coding of arbitrarily-shaped image/video objects; whereas its superior performance over the MPEG-4 LPE padding has been confirmed solidly. In the present paper, we propose to extend the use of SmartPad to all INTER frames (of arbitrary shapes), i.e., to use SmartPad to replace the zero padding scheme (as recommended in MPEG-4). Our simulation results show that a very substantial performance gain (3-7 dB) has been achieved, as compared to the MPEG-4 LPE/zero padding scheme.
Error Resilient Video Coding Using B Pictures in H.264

Since the quality of compressed video is vulnerable to errors, video transmission over unreliable Internet is very challenging today. Multi-hypothesis motion-compensated prediction (MHMCP) has been shown to have error resilience capability for video transmission, where each macroblock is predicted by a linear combination of multiple signals (hypotheses). B picture prediction is a special case of MHMCP. In H.264/AVC, the prediction of B pictures is generalized such that both of the two predictions can be selected from the past pictures or from the subsequent pictures. The multiple reference picture framework in H.264/AVC also allows previously decoded B pictures to be used as references for B picture coding. In this paper, we will discuss the error resilience characteristics of the generalized B pictures in H.264/AVC. Three prediction patterns of B pictures are analyzed in terms of their error-suppressing abilities. Both theoretical models (picture level error propagation) and simulation results are given for the comparison.
Comments on "A Novel Compression and Encryption Scheme Using Variable Model Arithmetic Coding and Coupled Chaotic System"

Recently, Bose and Pathak proposed a joint compression-encryption scheme by incorporating an adaptive arithmetic coder with a coupled chaotic system . In this comment, we first show that the scheme proposed by Bose and Pathak is not decodable. It is due to the fact that the current symbol to be encoded is swapped with a randomly selected symbol in the model prior to encoding it, making it impossible for the decoder to mirror the encoder's operations. We then suggest a natural solution to solve the undecodability problem by using the last encoded symbol to swap. Unfortunately, it can be shown that this modified scheme is vulnerable against a chosen-plaintext attack.
Motion estimation via hierarchical block matching and graph cut

Block matching based motion estimation algorithms are adopted in numerous practical video processing applications due to their low complexity. However, conventional block matching based methods process each block independently to minimize the energy function, which results in a local minimum. It fails to preserve the motion details. In this paper, we formulate the motion estimation as a labeling problem. The candidate labels are initialized by adopting a hierarchical block matching method. Then, we employ a graph cut algorithm to efficiently solve the global labeling problem with candidate labels. Experimental results show that the proposed approach can well preserve the motion details and outperforms all other block based motion estimation methods in terms of endpoint error and angle error on the Middleburry optical flow benchmark.
Model-based optimal dependent joint bit allocation of H.264/AVC statistical multiplexing

In this paper, we address the dependent joint bit allocation problem in H.264/AVC statistical multiplexing. For most of the existing methods, in order to improve the overall visual quality, the bit allocation is performed upon the relative complexities of different video programs. However, due to the temporal prediction employed in H.264, the influence of current frame to the rate-distortion (R-D) performances of the future frames should be taken in to account as well. The contributions of the paper are two-fold. First, a simple but accurate inter-frame dependency model (IFDM) is introduced which can quantitatively measure the coding dependency between the current coding frame and its reference frame. Second, based on the IFDM, the dependent joint bit allocation problem is revisited, and both the frame complexity and inter-frame dependency are considered in the bit allocation process. Then, it is proved that the dependent joint bit allocation problem can actually be relaxed into a convex optimization problem which can be optimally and efficiently solved. Experimental results demonstrate that the proposed dependent bit allocation method achieves 33.45% and 11.10% bitrate reduction on average compared with the equivalent bit allocation (EBA) and the optimal independent joint bit allocation (OIJBA) methods respectively.
PID-based real-time rate control

Many existing rate control schemes consider spatial quality only. As a result, this may introduce a large distortion variation over frames to which people are sensitive. In fact, people are also sensitive to temporal quality. We design a real-time rate control based on a PID controller to have better tradeoff between spatial and temporal quality. From different estimated number of bits per frame and buffer status, different target bits for each frame are used in order to reduce the flickering effect (smaller distortion variation) which is one factor affecting temporal quality. Experimental results suggest that our scheme can obtain more consistent quality while keeping high spatial quality.