nils-herrmann/clean_scirepeval huggingface dataset:
Image vector quantization using Hadamard transform subspace

A new technique for reduction of the dimensionality of an image vector quantizer is proposed. In this technique, the convention space domain distortion measure is replaced by a transform domain distortion measure. Due to the energy compaction properties of transforms such as cosine or Hadamard transforms, the dimensionality of the transform domain distortion measure can be reduced drastically without affecting the performance of the quantizer. A modified LBG algorithm incorporating the new distortion measure is proposed. The performance and design considerations of a real-time image encoder using the new technique are investigated. A four times speed up in both codebook design time and search time are obtained along with a four times reduction in the size of the fast RAM.<<ETX>>
Variable reconstruction scheme for distributed video decoding

Distributed Video Coding (DVC) is very different from traditional video coding structures due to its property of simple encoder and complex decoder. The generation of side information is a crucial part of DVC and has been attracting much attention, but research on the reconstruction also important for DVC is just a little. In current work, we propose a variable reconstruction scheme (VRS) by exploiting side information and the turbo decoded quantization bin efficiently. Simulation results demonstrate that the VRS gains up to 0.85 dB compared with the commonly used reconstruction scheme at the same bit rates and similar computation cost.
Web-based Beowulf-Class parallel computing on image database indexing and retrieval system

Content-based image retrieval (CBIR) techniques will be part of the next generation of search engines. However, even with a suitable retrieval method, real-time image retrieval from a large image database still requires extremely high computational power. In this paper, a Web-based image database indexing and retrieval system is described. It uses fast CBIR with Beowulf-Class parallel computing engine (Super Abacus) to efficiently and effectively shorten the retrieval time. Content-based image retrieval with several parallel algorithms for images which query different color spaces and the compressed-domain of the images are developed to achieve higher efficiency. Text-based query is also supported for images using a conventional annotation approach.
A novel small-cross-diamond search algorithm for fast video coding and videoconferencing applications

Search patterns and the center-biased characteristics of motion vector distribution (MVD) have a large impact on both searching speed and quality of block motion estimation. We propose a novel algorithm using two cross-shaped search patterns as the first two initial steps and large/small diamond-shaped patterns as the subsequent steps for fast block motion estimation (BME). The first small cross-shaped pattern is to fit the cross-center-biased MVD characteristics of the real-world sequences by evaluating the 5 relatively higher probable candidates located as a cross-shaped pattern at the search-grid center. The proposed small-cross-diamond search algorithm (SCDS) employs a halfway-stop technique and could find small motion vectors with much fewer points than the diamond search algorithm (DS) while maintains similar or even better quality. The speedup improvement of SCDS over DS can be up to 146%, i.e. 2.46 times faster than DS. Simulations show that SCDS is much more robust, provides faster searching speed and smaller distortions than other fast algorithms, typically very suitable for videoconferencing applications.
Point Oriented Hexagonal Inner Search For Fast Block Motion Estimation

Recently, an enhanced hexagon-based search (EHS) algorithm was proposed to speedup the original hexagon-based search (HS) by exploiting the group-distortion information of some evaluated points. In this paper, a second version of the EHS is proposed with a new point-oriented inner search technique which can further speedup the HS in both large and small motion environments. Experimental results show that the enhanced hexagon-based search version-2 (EHS2) is faster than the HS up to 34% with negligible PSNR degradation.
Horizontal Scaling and Shearing-Based Disparity-Compensated Prediction for Stereo Video Coding

In multiview video coding (MVC), disparity-compensated prediction (DCP) exploits the correlation among different views. A common approach is to use block-based motion-compensated prediction (MCP) tools to predict the disparity effect among different views. However, some regions in different views may have various deformations due to nonconstant depth. Thus, performance of DCP is not satisfactory with the simple translational model assumed in conventional block-based MCP tools. Previous attempts to achieve better disparity prediction were usually too complex for practical use. In this paper, horizontal scaling and shearing (HSS) effects are investigated to increase interview prediction accuracy for stereo video. HSS deformations are common among images of horizontally aligned views, due to horizontal and vertical flat surfaces that are not parallel with projection image planes. To achieve HSS-based DCP with minimal complexity, an efficient subsampled block-matching technique is adopted and integrated into MVC extension of H.264/AVC in stereo profile. Affine parameters estimation and additional frame buffers are not required and the overall increase of computational complexity and memory requirements are moderate. Experimental results show that the new technique can achieve up to 5.25% bitrate reduction in interview prediction using JM17.0 reference software implementation.
A novel rood-diamond search algorithm for fast block motion estimation

Search patterns and the center-biased characteristics of motion vector distribution (MVD) have large impact on both searching speed and quality of block motion estimation. In this paper, we propose a novel algorithm using a rood-shaped search pattern as the initial step and large/small diamond search patterns as the subsequent steps for fast block motion estimation (BME). The rood-shaped pattern is to fit the rood-center-biased MVD characteristics of the real-world sequences by evaluating the 9 relatively higher probable candidates located as a rood-shaped pattern at the search-grid center. The proposed rood-diamond search algorithm (RDS) employs halfway-stop technique and could find small motion vectors with fewer points than the diamond search algorithm (DS) while maintains similar or even better quality. The speedup improvement of RDS over DS can be up to 40% Simulations show that RDS is much more robust. provides faster searching speed and smaller distortions than other fast algorithms.
Text-driven automatic frame generation using MPEG-4 synthetic/natural hybrid coding for 2-D head-and-shoulder scene

In this paper, we propose a facial modeling technique based on the MPEG-4 synthetic/natural hybrid coding for automating frame sequence generation of a talking head. With the definition and animation parameters on a generic face object, the shape, textures and expressions of an adapted frontal face can generally be controlled and synchronized by the phonemes transcribed from plain text. By this developed facial modeling technique, it increases the intelligibility of an non-verbal facial communication for potential audiovisual lip-synch application on news reporting, lip-reading for the hearing-impaired or the deaf, virtual meeting through Internet, and story teller on demand (STOD).
A novel cross-diamond search algorithm for fast block motion estimation

In block motion estimation, search patterns with different shapes or sizes and the center-biased characteristics of motion-vector distribution have a large impact on the searching speed and quality of performance. We propose a novel algorithm using a cross-search pattern as the initial step and large/small diamond search (DS) patterns as the subsequent steps for fast block motion estimation. The initial cross-search pattern is designed to fit the cross-center-biased motion vector distribution characteristics of the real-world sequences by evaluating the nine relatively higher probable candidates located horizontally and vertically at the center of the search grid. The proposed cross-diamond search (CDS) algorithm employs the halfway-stop technique and finds small motion vectors with fewer search points than the DS algorithm while maintaining similar or even better search quality. The improvement of CDS over DS can be up to a 40% gain on speedup. Experimental results show that the CDS is much more robust, and provides faster searching speed and smaller distortions than other popular fast block-matching algorithms.
MPEG-7 dominant color descriptor using merged palette histogram similarity measure

The MPEG-7 dominant color descriptor (DCD) is an effective and compact representation of salient colors in an image region, which is very useful for content-based image retrieval applications. However, the DCD's modified quadratic histogram distance measure (QHDM) has shortcomings in fitting human perception similarity matching. A new merged palette histogram similarity measure is proposed to provide an alternative for the QHDM. The new similarity measure is based on a merged color palette as a common color space to define histogram intersection. Experimental results show that this new similarity measure provides more accurate and perceptually relevant image retrieval.
A fast block motion estimation using progressive partial distortion search

Real-time video applications, such as the speed-oriented videoconferencing require fast motion estimation while high quality video entertainments require motion estimation with small prediction error. In this paper, a novel block-matching algorithm for fast motion estimation named progressive partial distortion search algorithm (PPDS) is proposed. It uses a halfway-stop technique with progressive partial distortion (PPD) to increase the chance of early rejection of impossible candidate motion vectors at very early stages. Experimental results on different kinds of PPD show that PPDS provides a wide range of computational reduction from 19.37 to 62.39 times, with less than 1 dB degradation on PSNR performance as compared to the full search algorithm. It shows PPDS is suitable for a wide range of video applications. The proposed PPDS gives a compromised computational reduction from 28 to 38 times with only 0.34-0.50 dB degradation on PSNR performance as compared to the full search algorithm.
Compensated sum of absolute difference for fast H.264 inter mode selection

In this paper, a new compensated sum of absolute difference (CSAD) for fast H.264 inter mode selection algorithm is proposed. The main idea is to determine the best inter mode based on CSAD cost instead of the rate-distortion (RD) cost. This approach can avoid most of the computationally intensive processes in the H.264 mode decision. The CSAD could solve the problem of SAD and SATD costs used in mode decision which normally bias to the smaller block size modes. It is because they are normally achieving higher prediction accuracy but consume more bit rate. Experimental results show that the proposed CSAD-based mode decision algorithm can reduce 60% to 68% of the H.264 total encoding time with negligible degradation in the RD performance.
Enhanced hexagonal search for fast block motion estimation

Fast block motion estimation normally consists of low-resolution coarse search and the following fine-resolution inner search. Most motion estimation algorithms developed attempt to speed up the coarse search without considering accelerating the focused inner search. On top of the hexagonal search method recently developed, an enhanced hexagonal search algorithm is proposed to further improve the performance in terms of reducing number of search points and distortion, where a novel fast inner search is employed by exploiting the distortion information of the evaluated points. Our experimental results substantially justify the merits of the proposed algorithm.
An adaptive background biased depth map hole-filling method for Kinect

The launch of Kinect provides a convenient way to access the depth information in real time. However the depth map quality still needs to be enhanced for 3D visual applications. In this paper, an adaptive background biased depth map hole-filling method is proposed. First, depth holes caused by abnormal reflection are filled by color similarity in-painting, and a soft decision for color similarity checking is performed by the use of probabilities in random walks color segmentation. Afterwards it is assumed that the lost information in the rest of depth holes belongs to the background. The background depth information is extracted by automatic thresholding in the neighborhood of each hole. Depth holes are in-painted with the background information in their local neighborhood. Combination of color similarity in-painting and background biased in-painting is able to perform depth map hole-filling adaptively for different kinds of depth holes for Kinect. The hole-filling results and virtual view synthesis results show that the Kinect depth map quality can be improved significantly by the proposed method.
Low bit-rate video coding using 2-D adaptive sampling motion compensation

This paper presents a low bit-rate video coding algorithm based on variable block size motion estimation model to increase the prediction accuracy. To optimize the usage of motion vectors, a 2-D adaptive sampling structure is employed for merging those homogeneous motion fields together with minimum increase of prediction error. The motion compensated prediction error is also encoded adaptively using the hybrid VQ/DCT approach to cope with the motion field segmentation information of the current encoding frame. Experimental results show that the proposed scheme can better utilize the limited bit budget for motion compensation than classical block matching techniques and those annoying blocking artifacts can be alleviated.
Enhanced adaptive intra mode bit skip for H.264/AVC

Adaptive intra mode bit skip (AIMBS) can improve the coding efficiency of intra coding in H.264/AVC. However, it has two shortcomings: one is that DC mode is not effectively handled in AIMBS as DC mode is duplicated in both Single-Prediction and Multiple-Prediction processing; the other is that AIMBS does not well match the most probable mode (MPM) estimation scheme of H.264/AVC. To tackle these two shortcomings, an enhanced AIMBS (EAIMBS) scheme with larger bitrate reduction and better QP robustness is presented. In addition, EAIMBS almost maintains as low computational complexity as AIMBS. The proposed technique introduces distance-based weighted prediction (DWP) to replace DC mode in Multiple-Prediction and it calculates the MPM by simplified L-shaped most probable mode estimation (SLMPME) method. Experimental results show that EAIMBS gives in average 3.97% bit-rate reduction and 51% computation reduction at QP=32 compared with H.264/AVC.
Preprocessing for discrete multiwavelet transform of two-dimensional signals

Multiwavelet transform can be implemented by a tree-structured matrix filter bank, which operates on vector sequence input instead of scalar ones. Therefore, unlike in a scalar wavelet system, preprocessing is usually required to extract vector sequence input from the input signal for better performance. A 2-D approximation-based preprocessing scheme for GHM (Geronimo, Hardin and Massopust) discrete multiwavelet transform of 2-D signals is proposed. Compared with the recent 1-D approximation-based method, the proposed scheme reduces the preprocessing computational complexity by 65% while maintaining similar energy compression ability.
A foreground biased depth map refinement method for DIBR view synthesis

The performance of view synthesis using depth image based rendering (DIBR) highly depends on the accuracy of depth map. Inaccurate boundary alignment between texture image and depth map especially for large depth discontinuities always cause annoying artifacts in disocclusion regions of the synthesized view. Pre-filtering approach and reliability-based approach have been proposed to tackle this problem. However, pre-filtering approach blurs the depth map with drawback of degradation of the depth map and may also cause distortion in non-hole region. Reliability-based approach uses reliable warping information from other views to fill up holes and is not suitable for the view synthesis with single texture video such as video-plus-depth based DIBR applications. This paper presents a simple and efficient depth map preprocessing method with use of texture edge information to refine depth pixels around the large depth discontinuities. The refined depth map can make the whole texture edge pixels assigned with foreground depth values. It can significantly improve the quality of the synthesized view by avoiding incorrect use of foreground texture information in hole filling. The experimental results show the proposed method achieves superior performance for view synthesis by DIBR especially for large baseline.
A Linear Prediction Based Fractional-Pixel Motion Estimation Algorithm

In modern video coding standards, for example H.264, fractional-pixel motion estimation (ME) is implemented. Many fast integer-pixel ME algorithms have been developed to reduce the computational complexity of integer-pixel ME. With these advancements, fractional-pixel ME becomes the new bottleneck in the implementation of video encoders. For example, the conventional hierarchical fractional-pixel search (HFPS) at quarter-pixel accuracy requires computing the distortions of at least 16 fractional-pixel positions. This computation is comparable to or even higher than advanced fast integer-pixel ME process. Fast fractional-pixel ME algorithms were therefore developed, in which initial search point is first predicted before applying fast refinement search. Parabolic error surface model and fractional-pixel motion vector information of neighboring blocks are commonly used for initial search point prediction but they have problems of unsolvable solution and uncorrelated motion vectors, respectively. To tackle these problems, a center-biased fast fractional-pixel ME algorithm using linear prediction based search with intrinsic center-biased characteristic is developed in this paper. Experimental results show that the proposed algorithm is fast and robust.
Lossless wavelet image coding using layered coefficient partitioning

A layered coefficient partitioning (LCP) scheme, which splits integer wavelet coefficients into multiple layers is introduced. The multilayer approach provides a better way to exploit the correlation among the coefficients. An image coding algorithm based on LCP is presented. The proposed algorithm gives improvement in both the lossless and lossy coding performance over the existing wavelet transform based lossless image coders. Experimental results show that the proposed LCP coder produces lossless rates competitive to some of the best performing spatial domain lossless coding schemes and constantly outperforms other multirate coders such as S+P and JPEG-2000 by about 3%-4%. The lossy performance improvement is about 1 to 3 dB (PSNR) in the 0.2 to 3.2 bpp range as compared with the S+P coder.
A Novel Motion Estimation Method Based on Structural Similarity for H.264 Inter Prediction

In the motion estimation of H.264, the best matching blocks and the best prediction modes are chosen by Lagrange cost function whose distortion metric is the sum of absolute (transformed) differences [SA(T)D] which has similar meaning with MSE or PSNR. Recently a new image measurement called structural similarity (SSIM) based on the degradation of structural information was brought forward. It is proved that the SSIM can provide a better approximation for the perceived image distortion than the currently used PSNR (or MSE). In this paper, we propose an improved motion estimation method based on SSIM (MEBSS) for H.264 inter coding. Experiment results show that the MEBSS can reduce average 20% bit rate and 2% encoding time while maintaining the same perceptual video quality, and the maximum reduction in bitrate is more than 50%
A new center-biased search algorithm for block motion estimation

Experimental results show that the block motion field of a real world image sequence is usually gentle, smooth, and varies slowly, as a result in a center-biased global minimum motion vector distribution instead of an uniform distribution. Based on this characteristic of the image sequence a new four-step search (4SS) algorithm with a center-biased checking point pattern for fast block motion estimation is proposed. A variable searching-step technique is employed in the proposed algorithm with a minimum of 2 searching steps and a maximum of 4. The total number of checking points is varied from 17 to 27. Simulation results show that, as compared to the well-known three-step search, the proposed 4SS produces smaller motion compensation errors with a smaller computational requirement. The 4SS also possesses hardware-oriented features regularity and simplicity.
Integer multiwavelet transform for lossless image coding

The integer Haar wavelet transform or S-transform is used as the basic building block for many integer wavelet transforms. As an alternative, a new integer multiwavelet transform and its associated integer prefilter are designed based on a box-and-slope multi-scaling system. Both the transform and prefilter can be implemented with a simple integer Haar transform requiring only addition and bit shift operations. Since the new integer transform is an approximation to a nontrucated transform with a higher vanishing moment than that of a Haar transform, better approximation accuracy is expected and verified experimentally. The transform is successfully applied to lossless image coding with results outperforming that of lossless JPEG and S-transform.
A hierarchical block motion estimation algorithm using partial distortion measure

Most of the hierarchical block matching algorithms reduce computation by matching only some of the locations inside the search area. In this paper, we propose a novel hierarchical partial distortion search (HPDS) algorithm which reduces the computation of each distortion measure instead of the number of checking points by using partial distortion measure. Experimental results show that the proposed algorithm provides 6 times speed up as compared with full search while maintains the MSE performance very close to full search. Moreover, it can also achieve 20 times speed up when the MSE performance is kept close to the well-known three-step search. With appropriate parameter selections, the proposed algorithm can fit HDTV and MPEG-2 applications where high motion estimation accuracy is required, or real-time video conferencing applications where encoding speed is critical.