nils-herrmann/clean_scirepeval huggingface dataset:
A new palette histogram similarity measure for MPEG-7 dominant color descriptor

The MPEG-7 dominant color descriptor (DCD) is an effective, compact, and intuitive representation of salient colors in an image region and is very useful for content-based image retrieval and indexing applications. However, the original quadratic histogram distance measure (QHDM) for MPEG-7 DCD similarity matching does not fit the human perception very well. It may cause incorrect ranks between regions with similar salient color distributions. In this paper, 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 provide better accurate and perceptually relevant image retrieval for MPEG-7 DCD.
Enhanced Diamond Search Using Four-Corner-Based Inner Search For Fast Block Motion Estimation

This paper proposes a very efficient and simple fine-resolution inner search for the well-known diamond search (DS) algorithm. Based on the local unimodal error surface assumption, a new 4-corner-based inner search technique is proposed to speedup the original DS in both large and small motion environments by exploiting the group-distortion information of some evaluated points. Experimental results show that the enhanced diamond search (EDS) is faster than the original DS up to 30% with negligible PSNR degradation
Multiple block-size search algorithm for fast block motion estimation

Although variable block-size motion estimation provides significant video quality and coding efficiency improvement, it requires much higher computational complexity compared with fixed block size motion estimation. The reason is that the current motion estimation algorithms are mainly designed for fixed block size. Current variable block-size motion estimation implementation simply applies these existing motion estimation algorithms independently for different block sizes to find the best block size and the corresponding motion vector. Substantial computation is wasted because distortion data reuse among motion searches of different block sizes is not considered. In this paper, a motion estimation algorithm intrinsically designed for variable block-size video coding is presented. The proposed multiple block-size search (MBSS) algorithm unifies the motion searches for different block sizes into a single searching process instead of independently performing the search for each block size. In this unified search, the suboptimal motion vectors for different block sizes are used to determine the next search steps. Its prediction quality is comparable with that obtained by performing motion search for different block sizes independently while the computational load is substantially reduced. Experimental results show that the prediction quality of MBSS is similar to full search.
A novel ordered-SPIHT for embedded color image coding

The magnitude distribution law of DWT coefficients of color image data in Karhunen-Loeve space is investigated. Considering the KLT matrix formed, the magnitude of DWT coefficients in components K/sub 1/, K/sub 2/ and K/sub 3/, in general, have the relation K/sub 1/>K/sub 2/>K/sub 3/ where K/sub 1/, K/sub 2/, K/sub 3/ are the three components of a color image in KL space. Based on this characteristic and other DWT coefficient features, a novel ordered-SPIHT for embedded color image coding (OCSPIHT) is proposed in this paper. The set of DWT coefficients of an image in KL space are split into several sets according to their magnitudes. For each specific threshold, only the sets with coefficients equal to or larger than the threshold will be encoded. This can save many bits and improve coding performance especially at low bit rate.
Successive partition zero coder for embedded lossless wavelet-based image coding

A new embedded lossless wavelet-based image coding algorithm called successive partition zero coder (SPZC) which uses both horizontal and vertical bit scanning is proposed. Experimental results show that SPZC outperforms other state-of-the-art coders such as LJEG, SPIHT and CREW etc. In term of coding efficiency by successive partition the wavelet coefficients in the space-frequency domain and noncausal adaptive context modeling.
Block-Matching Translation and Zoom Motion-Compensated Prediction

In modern video coding standards, motion compensated prediction (MCP) plays a key role to achieve video compression efficiency. Most of them make use of block matching techniques and assume the motions are pure translational. Attempts toward a more general motion model are usually too complex to be practical in near future. In this paper, a new Block-Matching Translation and Zoom Motion-Compensated Prediction (BTZMP) is proposed to extend the pure translational model to a more general model with zooming. It adopts the camera zooming and object motions that becomes zooming while projected on video frames. Experimental results show that BTZMP can give prediction gain up to 2.25dB for various sequences compared to conventional block-matching MCP. BTZMP can also be incorporated with multiple reference frames technique to give extra improvement, evidentially by the prediction gain ranging from 2.03 to 3.68dB in the empirical simulations.
Improved Inter Prediction based on Structural Similarity in H.264

H.264 achieves higher compression efficiency by employing multiple modes inter prediction, rate-distortion (RD) optimal mechanism and other new techniques. Distortion metric plays an important role in video compression performance. Structural similarity (SSIM) is a new image quality assessment method, which is more consistent with Human Vision Systems (HVS). So in this paper, we propose to adopt SSIM as the distortion metric in the inter prediction cost functions, named "improved inter prediction method based on SSIM" (IPBSS). It is an improved method of our previous work MEBSS. Simulation results indicate that the IPBSS can averagely save bit rate more than 13% while maintaining the almost same video quality with QP = 10, 20 and 30. That is a better result than our previous work MEBSS.
Bit Rate Estimation for Cost Function of 4×4 Intra Mode Decision of H.264/AVC

H.264/AVC is a newest international video coding standard that can achieve considerably higher coding efficiency than previous standards. This comes at the cost of the complex mode decision procedure using the rate-distortion optimization, which makes real-time encoding difficult. To reduce the complexity of rate-distortion cost, we propose a bit rate estimation technique to avoid the entropy coding method during mode decision of intra prediction. The estimation method is based on the properties of context-based variable length coding (CAVLC). Simulation results demonstrate that the proposed estimation method achieves up to 53 % reduced encoding time of intra coding with ignorable degradation of coding performance.
Enterprise Bankruptcy Prediction Using Noisy-Tolerant Support Vector Machine

Enterprise bankruptcy forecasting is very important to manage credit risk and a lot of scholars applied themselves to study how to increase the accuracy of bankruptcy forecast which requires a powerful learning machine algorithm capable of good generalization on financial data. Therefore, classification algorithms like support vector machine (SVM) are popular for modeling and predicting corporate distress. However, making inferences and choosing appropriate responses based on incomplete, uncertainty and noisy data is challenging in financial settings particularly in bankruptcy prediction. In this paper, we propose a new approach for enterprise bankruptcy prediction, which uses a novel support vector machine and K-nearest neighbor (KNN-SVM) to remove noisy training examples. The experimental results show that the generalization performance and the accuracy of classification are improved significantly compared to that of the traditional SVM classifier, and adapt to engineering applications.
A lossless multi-partitioning successive zero coder for wavelet-based progressive image transmission

This paper proposed an embedded image compression algorithm called lossless multi-partitioning successive zero coder (LMP-SZC) using the integer wavelet transform for progressive image transmission (PIT). By dynamically adjusting the partitions based on the space-frequency domain coefficients, our algorithm can achieve lower complexity and superior coding efficiency as compared with other well-known embedded lossless wavelet-based coder even without the zerotree analysis.
Speeding up fractal image encoding by wavelet-based block classification

The authors propose a novel fast fractal image encoding algorithm using wavelet-based block classification. The range blocks and corresponding domain blocks are classified into edge selective categories by the energy compacted wavelet coefficients. The searching is carried out between the same classes for range domain comparisons which significantly reduces the computational complexity. Experimental results show that the proposed method can speed up the fractal image encoding process by up to 12.3 times over the conventional full search method.
Super abacus: a Beowulf class parallel computer for multimedia signal processing research

A few thousands years ago, Chinese people used small rods connected to movable counters such as beads to construct a low-cost calculation device, which is called Abacus. Today, Beowulf-class parallel computer using such similar approach to construct a low-cost supercomputing system, in which Pentium-based computers (beads) are connected by a Fast Ethernet switch (rods) to form a parallel supercomputer. This paper presents our experiences learnt from the construction of a 17-node Beowulf-class cluster called Super Abacus. The system is designed to provide high computational power for handling real-time multimedia signal processing such as audio/video compression, multimedia database searching and content-based audio/video classification so as to support multimedia signal processing research projects in CityU Image Processing Laboratory. The technologies and methodologies to achieve the goal of lower system cost with better performance will be described.
Depth-aided exemplar-based hole filling for DIBR view synthesis

Quality of synthesized view by Depth-Image-Based Rendering (DIBR) highly depends on hole filling, especially for synthesized view with large disocclusion. Many hole filling methods are proposed to improve the synthesized view quality and inpainting is the most popular approach to recover the disocclusions. However, the conventional inpainting either makes the hole regions blurred via diffusion or propagates the foreground information to the disoclusion regions. Annoying artifacts are created in the synthesized virtual views. This paper proposes a depth-aided exemplar-based inpainting method for recovering large disoclusion. It consists of two processes, warped depth map filling and warped color image filling. Since depth map can be considered as a grey-scale image without texture, it is much easier to be filled. Disoccluded regions of color image are predicted based on its associated filled depth map information. Regions with texture lying around the background have higher priority to be filled than other regions and disoccluded regions are filled by propagating the background texture through the exemplar-based inpainting. Thus artifacts created by diffusion or using foreground information for prediction can be eliminated. Experimental results show texture can be recovered in large disocclusions and the proposed method has better visual quality compared to existing methods.
A new motion compensation method using superimposed inter-frame signals

A new MCP method called Neighbor Predicted Superimposed Search (NPSS) algorithm that uses superimposed inter-frame signals to achieve higher prediction accuracy is proposed in this paper. It outperforms other Multi-Hypothesis MCP (MHMCP) methods as it does not require the transmission of multiple motion vectors. The proposed method has better prediction quality and yet having comparable computational complexity as conventional block-based MCP with no extra side-information overhead.
Six-digit stroke-based Chinese input method

During the last three decades, more than one thousand Chinese input methods have been developed. However, people are still looking for better input methods in terms of easy to use, easy to remember, high input speed and small keypad implementation on handheld devices. The well-known stroke-based Chinese input method using only five basic stroke types could achieve low learning curve and small numeric keypad implementation but its input speed is limited for complex Chinese characters with a lot of strokes. To tackle this problem, simplified stroke-based Chinese character and phrase coding methods using (3+3) rules are proposed in this paper. The proposed method only uses the first 3 stroke codes and the last 3 stroke codes to represent the first and last radical information of the character for achieving lower average code length and higher hit rate of first character on the candidate list. To further enhance the input speed, a very user-friendly (3+3) phrase coding rule is also proposed for inputting Chinese phrases in terms of 2-character, 3-character and long-character phrases. Three special key assignment designs are developed for practical implementation of the proposed Chinese character and phrase input method using conventional QWERTY keyboard, PC's numeric keypad and mobile phone 12-key keypad. Experimental results have shown that the proposed character coding can achieve lower average code length and higher Hit Rate of First Character as compared with conventional stroke-based method and some well-known Chinese input methods. The proposed coding rules are also very easy to use and remember.
Novel cross-diamond-hexagonal search algorithms for fast block motion estimation

We propose two cross-diamond-hexagonal search (CDHS) algorithms, which differ from each other by their sizes of hexagonal search patterns. These algorithms basically employ two cross-shaped search patterns consecutively in the very beginning steps and switch using diamond-shaped patterns. To further reduce the checking points, two pairs of hexagonal search patterns are proposed in conjunction with candidates found located at diamond corners. Experimental results show that the proposed CDHSs perform faster than the diamond search (DS) by about 144% and the cross-diamond search (CDS) by about 73%, whereas similar prediction quality is still maintained.
A Compact and Efficient Color Descriptor for Image Retrieval

An important problem in color based image retrieval is the lack of efficient way to represent both the color and the spatial structure information with single descriptor. To solve this problem, a new dominant color structure descriptor (DCSD), is proposed. The descriptor combines the compactness of dominant color descriptor (DCD) and the accuracy of color structure descriptor (CSD) to enhance the retrieval performance in a highly efficient manner. The feature extraction and similarity measure of the descriptor are designed to address the problems of the existing descriptors such as color inaccuracy of DCD and redundancy of CSD. Experimental results show that DCSD has a significant improvement in retrieval performance and descriptor size over DCD. An eight-color DCSD (DCSD 8) gives an averaged normalized modified retrieval rate (ANMRR) of 0.0993 using MPEG-7 common color dataset, outperforming compact configurations of scalable color descriptor and color structure descriptor with smaller descriptor size.
Fast Bit Rate Estimation for Mode Decision of H.264/AVC

To achieve the highest coding efficiency, H.264/AVC uses rate-distortion optimization technique. This means that the encoder has to code the video by exhaustively trying all the mode combinations including the different intra- and inter-prediction modes. Therefore, the complexity and computation load of video coding in H.264/AVC increase drastically compared to any previous standards. To reduce the complexity of rate-distortion cost computation, we propose a fast bit rate estimation technique to avoid the entropy coding method during intra- and inter-mode decision of H.264/AVC. The estimation method is based on the properties of context-based variable length coding (CAVLC). The proposed rate model predicts the rate of a 4 times 4 quantized residual block using five different tokens of CAVLC. Experimental results demonstrate that the proposed estimation method reduces about 47% of total encoding time on using intra-modes only and saves about 34% of total encoding time on using both inter- and intra-modes with ignorable degradation of coding performance when the fast motion search algorithm is used. When full search motion estimation algorithm is used, the proposed algorithm reduces about 17% of total encoding time.
Stretching, compression and shearing disparity compensated prediction techniques for stereo and multiview video coding

In multiview video coding, disparity compensated prediction exploits the correlation among different views. A common approach is to use the conventional motion compensated prediction to predict disparity effect among different views. However, the same object in different views usually has deformation of different extents and, thus, accurate disparity prediction cannot be achieved with such simple translational motion model. Previous attempts to achieve more accurate disparity prediction are usually too complex for practical implementation. In this paper, stretching, compression and shearing (SCSH) effects are investigated to better model the disparity effect in disparity compensated prediction. To achieve SCSH effects with minimal computation, an efficient disparity compensated prediction using subsampled block-matching technique is proposed. No affine parameters estimation or additional frame buffers is required and the overall increase in memory requirement and computational complexity is moderate. Experimental results show that the new technique can achieve up to 4.84% bitrate reduction in inter-view prediction using JM17.0 reference software implementation.
A novel multiwavelet-based integer transform for lossless image coding

Integer Haar wavelet transform or S-transform is used as the basic building block for many exiting integer wavelet transform. As an alternative, a new integer multiwavelet transform and its associated integer prefilter are designed based on box-and-slope multi-scaling system. Both the transform and prefilter can be implemented with simple integer Haar transform requiring only addition and bit shift operations. Since the new integer transform is an approximation to nontruncated transform with higher vanishing moment than that of 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.
Block-Matching Translation And Zoom Motion-Compensated Prediction by sub-sampling

In modern video coding standards, motion compensated prediction (MCP) plays a key role to achieve video compression efficiency. Most of them make use of block matching techniques and assume the motions are pure translational. Some attempts toward a more general motion model usually too complex to be practical in near future. In this paper, a new Block-Matching Translation and Zoom Motion-Compensated Prediction (BTZMP) is proposed to extend the pure translational model to a more general model with zooming in a practical way. It adopts the camera zooming and object motions that becomes zooming while projected on the video frames. The proposed BTZMP significantly improve motion compensated prediction. Experimental results show that BTZMP can give prediction gain up to 1.09dB compared to conventional sub-pixel block-matching MCP. In addition, BTZMP can be incorporated with Multiple Reference Frames (MRF) technique to give extra improvement, evidentially by the prediction gain ranging up to 2.08dB in the empirical simulations.
Efficient subtree splitting algorithm for wavelet-based fractal image coding

In this paper, a novel wavelet subtree splitting algorithm is proposed, which divides a subtree into scalar quantized wavelet coefficients and fractal coded sub-subtree. Based on this new technique, a variable size wavelet subtree fractal coding scheme for still image compression is developed. Experimental results show that the new scheme can achieve nearly optimal partition of wavelet subtree with substantially computational reduction as compared with Davis' scheme.
Edge-Based Structural Similarity for Image Quality Assessment

Objective quality assessment has been widely used in image processing for decades and many researchers have been studying the objective quality assessment method based on human visual system (HVS). Recently the structural similarity (SSIM) is proposed, under the assumption that the HVS is highly adapted for extracting structural information from a scene, and simulation results have proved that it is better than PSNR (or MSE). By deeply studying the SSIM, we find it fails in measuring the badly blurred images. Based on this, we develop an improved method which is called edge-based structural similarity (ESSIM). Experiment results show that ESSIM is more consistent with HVS than SSIM and PSNR especially for the blurred images
A new cross-diamond search algorithm for fast block matching motion estimation

In order to fit the small cross-center-biased characteristic of the real world video sequences, an improved version of the well-known cross diamond search algorithm is proposed in this paper. The new algorithm uses a small cross-shaped search patterns in the first two steps to speedup the motion estimation of stationary and quasi-stationary blocks. Experimental results show that this new cross-diamond search algorithm could achieve much higher computational reduction as compared with Diamond Search (DS) and Cross Diamond Search (CDS) while similar prediction accuracy is maintained, and it is especially suitable for videoconferencing sequences.
A new center-biased orthogonal search algorithm for fast block motion estimation

A new center-biased orthogonal search algorithm (CBOSA) for fast block-based motion estimation is proposed. The new algorithm uses a center-biased search point pattern, which is based on center-biased motion vector distribution characteristic of the real-world image sequences, for improving the performance of the conventional orthogonal search algorithm (OSA). Simulation results show that the proposed CBOSA performs better than the OSA and the well-known three-step search in terms of compensation errors and search points requirement. In addition, the CBOSA also reduces the worst case search points requirement of the center-biased search algorithms from 33 of the new three-step search and 27 of the four-step search to 15 search points.
Text-driven automatic image sequence generation using facial modeling for digital TV news production system

This paper presents a facial modeling approach for automating the head-and-shoulder image sequence generation for digital TV news video clips production which is the most expensive part in terms of manpower and cost. With the IPA phonetics transcribed from news script being the driving parameter, the high precision adapted 2-D wireframe model on a frontal view of speaker image with sufficient facial textural information will be used to define the associated facial action units (AFAUs) corresponding to the phonemes. This developed facial modeling approach increases the intelligibility of facial non-verbal communication for potential audiovisual lip-synch application like TV news video clips, video telephony, Story Teller On Demand (STOD), lip-reading for the deaf or the hearing-impaired.