Diamond Search Algorithm Research Articles

An efficient VLSI architecture for fast motion estimation by hybridizing parallel spiral and adaptive threshold star diamond search algorithm‐based search algorithm in HEVC

SummaryThis article proposes a high efficiency video coding (HEVC) standard hardware using block matching motion estimation algorithm. A hybrid parallel spiral and adaptive threshold star diamond search algorithm (Hyb PS‐ATSDSA) proposes for fast motion estimation in HEVC. Parallel spiral search approach utilizes spiral pattern for searching from center to the surroundings and adaptive threshold SDA consists of two phases, they are adaptive threshold and star diamond algorithm. To lower computational complexities in HEVC architecture, parallel spiral search algorithm uses several blocks matching schemes. Adaptive threshold and star diamond algorithm are used to reduce the matching errors and remove the invalid blocks early from the procedure of motion estimation and finally predicts the final motion of the image. Speed is increased while using this hybrid algorithm. Proposed structure is carried out in Xilinx; ISE 14.5 design suit, then the experimental outcomes are analyzed to existing motion estimation strategies in field‐programmable gate array devices. Experimental performance of the proposed Hyb‐PS‐ATSDSA‐ME‐HEVC method attains lower delay 33.97%, 32.97%, 62.97, and 26.97%, and lower area 34.867%, 45.97%, 27.97%, and 43.967% compared with the existing methods, such as FSA‐ME‐HEVC, TZSA‐ME‐HEVC, hyb TZSA‐IME‐HEVC, and IBMSA‐ME‐HEVC, respectively.

Advanced framework for enhancing ultrasound images through an optimized hybrid search algorithm and a novel motion compounding processing chain

Ultrasound imaging is a fast, widespread, and essential diagnostic technique for examining the body’s internal anatomy to find abnormal tissues or diseases. However, speckle noise in ultrasound imaging corrupts fine details and edges and degrades the image’s resolution and contrast, making diagnosing more difficult. In this work, a speckle reduction method using motion compounding is proposed. The objective of this work is ultrasound image enhancement keeping all the diagnostics details and edges. The proposed method uses the pre-locations frames that the sonographer generates before locating the required diagnostic frame. These frames are applied to the proposed optimized Modified Three-Step Search (O-MTSS) algorithm to enhance the final processed frame. The O-MTSS algorithm is a hybrid between the Three Step Search algorithm (TSS) and the New Diamond Search Algorithm (NDS). The method requires a scoring layer for storing additional frames to select optimal frames that will be used for enhancement. The proposed methodology is tested on synthetic and real ultrasound images. The outcomes produce considerable speckle reduction while maintaining the image edges with good computational time for real-time scanning. The result is evaluated by subjective physicians, radiologists, and image evaluation metrics. According to the percentages of the subjective analysis, there is a remarkable improvement in the processed image. The proposed algorithm result is compared with existing algorithms; It is observed that the improvement in terms of signal to noise ratio, peak signal to noise ratio, mean square error, root mean square error and structural similarity index values of the proposed method are 4.6%, 3.32%, 12.02%, 6.2% and 1.57% respectively over Non-Local Low-Rank (NLLR) method. According to qualitative and quantitative analysis, the suggested method outperforms existing speckle reduction techniques regarding edge and fine detail preservation.

Correction to: An Efficient VLSI Architecture for Fast Motion Estimation Exploiting Zero Motion Prejudgment Technique and a New Quadrant-Based Search Algorithm in HEVC

In this manuscript, new quadrant-based search algorithm with zero motion prejudgment is proposed for motion estimation (ME) in HEVC (High Efficiency Video Coding) standard. The HEVC standard is used to obtain efficient output with low motion estimation time. The proposed quadrant-based search algorithm is a fast block matching algorithm that obtain better block matching amid the current block and reference block. The zero motion prejudgment (ZMP) method is used to find the block, whether it is motion or static and it is used for decreasing the computational complexity (CC) in the proposed quadrant-based search algorithm. The proposed quadrant-based search algorithm with ZMP technique for motion estimation in HEVC is implemented on the FPGA hardware platform. The entire architecture is executed in Verilog HDL with Virtex-5 technology and integrated with Xilinx ISE Design Suite 14.5. The results are integrated into the CIF (352 × 288 pixels) and HD (1280 × 720 pixels) video input sequence. The evaluation metrics like PSNR, Motion estimation time, sum of absolute difference (SAD) value are analyzed with existing method like hexagon, adaptive root pattern algorithm, and diamond search algorithm. Then the hardware parameters like power consumption and maximum operating frequency are measured. The hardware utilization is reduced and the power consumption of the proposed model is diminished to 0.143 W. The maximal operating frequency of the proposed model is 440.470 MHz. The experimental outcomes demonstrate that the proposed motion evaluation approach in HEVC is more effective than existing algorithms.

An efficient field-programmable gate array-based hardware oriented block motion estimation algorithm based on diamond adaptive rood pattern search algorithm for multi-standard video codec

Motion estimation and motion compensation techniques are effectively used for removing temporal redundancy between adjacent frames during video compression, but video quality will be degraded with the traditional pixel-based matching algorithms. To overcome this issue, diamond adaptive rood pattern search algorithm-based block-matching motion estimation algorithms are proposed in this manuscript for multi-stranded codec hardware design, which provide a high compression rate with less computational complexity. In this work, a diamond adaptive rood pattern search algorithm is used, which is a combination of a diamond-search algorithm and adaptive rood pattern search. In addition, the proposed algorithm applies multiple search strategies and terminates unnecessary searching while reserving high data regularity. The proposed diamond adaptive rood pattern search algorithm-based block-matching motion estimation algorithm for multi-stranded codec hardware design provides good performance in terms of complex calculations reduction and reaches a high speed in comparison to traditional search algorithms. The proposed architecture is implemented in Xilinx ISE design 14.5 suite and the implemented results are compared to the existing motion estimation techniques on field-programmable gate array devices. Simulation results shows that the diamond adaptive rood pattern search algorithm for multi-stranded codec hardware design provides a very good improvement in terms of computations overhead reduction, with 96.4%, 97.3% latency and 98.7% throughput and achieves a high compression rate without video quality degradation.

A New Low Complexity Bit-truncation Based Motion Estimation and Its Efficient VLSI Architecture

A new motion estimation method and its hardware implementation are presented in this paper. In this method, all the frames are firstly gray coded. After that, the two most significant bits from the current frame and reference frame are used to compute the motion vector. Besides, a diamond search algorithm is used in place of the full-search algorithm. The motion estimation scheme proposed in the present paper is also verified to work on various standard video sequences. The experimental results thus obtained show that the proposed algorithm has an excellent balance of performance and computational complexity. External memory access has been reduced drastically by incorporating search pixel reuse. The resulting architecture is simple in terms of the hardware cost and power requirements while being faster than a recently reported similar architecture. The proposed architecture requires less hardware than comparable systems without compromising performance. The proposed architecture is therefore suited to be used in portable consumer electronic devices with real-time video applications in which power consumption is a concern.

Prediction-biased diamond search algorithm: a new approach to reduce motion estimation complexity

Prediction-biased diamond search algorithm: a new approach to reduce motion estimation complexity

Improved Particle Swarm Optimization Approach for Vibration Vision Measurement

Traditional template matching-based motion estimation is a popular but time-consuming method for vibration vision measurement. In this study, the particle swarm optimization (PSO) algorithm is improved to solve this time-consumption problem. The convergence speed of the algorithm is increased using the adjacent frames search method in the particle swarm initialization process. A flag array is created to avoid repeated calculation in the termination strategy. The subpixel positioning accuracy is ensured by applying the surface fitting method. The robustness of the algorithm is ensured by applying the zero-mean normalized cross correlation. Simulation results demonstrate that the average extraction error of the improved PSO algorithm is less than 1%. Compared with the commonly used three-step search algorithm, diamond search algorithm, and local search algorithm, the improved PSO algorithm consumes the least number of search points. Moreover, tests on real-world image sequences show good estimation accuracy at very low computational cost. The improved PSO algorithm proposed in this study is fast, accurate, and robust, and is suitable for plane motion estimation in vision measurement.

A New Pentagon Search Algorithm for Fast Block-Matching Motion Estimation

The impact of search pattern is a crucial part in the block-based motion estimation for finding the motion vector. An issue of distortion performance and search speed heavily depends upon the size and shape of search strategy applied. Performing the deep analysis for motion vector distribution on standard test videos, it is desirable to have such type of algorithm that meets the requirement of searching motion vector in less time. Hence, a new kind of Pentagon algorithm is proposed in this paper for fast block-matching motion estimation (BMME). It is an easy and efficient technique for finding motion vector. Experimental results expose the proposed Pentagon algorithm sparsely surpass the noted Diamond search (DS) algorithm. The new Pentagon search algorithm is examined with the previously proposed Diamond search algorithm in terms of performance measure; the proposed algorithm attains better performance with the less complexity. The experimental examination also depicts that the pentagon algorithm is better than the previously proposed Diamond search (DS) in terms of mean-square error performance and required the number of search points. The overall speed improvement rate (SIR) is about 31% with respect to the DS.

УСОВЕРШЕНСТВОВАНИЕ ОЦЕНКИ ДВИЖЕНИЯ В ВЫСОКОЭФФЕКТИВНОМ ВИДЕОКОДИРОВАНИИ

The paper deals with video coding based on the use of dependent sources, which is caused by the need to accelerate the coding process. The coding time is directly dependent on the computing power, which with the advent of new standards is not enough. Therefore, the article suggests the results of the study, which are designed to improve existing methods, as well as to continue the progress of scientific research in this area. The results consist of using an approach to compression based on coding methods of dependent sources, which can significantly reduce the complexity of processing on the side of the encoder. The results of the study were obtained using two coding algorithms for fixed and dynamic plots. For comparison, JPEG and, respectively, MPEG encoding standards were defined, as well as an improved algorithm that was considered by the authors in previous papers. It solves the problem of efficiently recovering intermediate frames on the decoder side. When evaluating the movement, search styles have a significant impact on the performance of the algorithm, both the search speed and the quality of the search. The search style should be designed considering the characteristics of the distribution of the motion vector probability (MVP) of the sequences of the real plot. The purpose of this study is to improve the coding efficiency of video sequences using the Diamond Search (DS) algorithm. The results show that DS is efficient and reliable, it can always give a higher search speed in different sequences than other algorithms.

Complexity reduction for HEVC encoder using multiplication free one-bit transformation

In high-efficiency video coding (HEVC), motion estimation (ME) complexity is high. The ME complexity is greatly reduced by implementing a multiplication free one-bit transform (MF-1BT) in the HEVC encoder. Compared with the other one-bit transforms, the computational load of MF-1BT is less. The implementation of MF-1BT in a HEVC encoder greatly reduces the ME complexity in terms of ME time (MET) and total encoding time (ET). Experimental results show that the MF-1BT along with full search reduces the ME complexity in terms of percentage reduction in MET and ET by 89.03% and 87.53%, respectively, as compared with a conventional full search algorithm with a Bjontegaard delta-rate (BD-rate) of 0.1095% and Bjontegaard delta-peak signal-to-noise ratio (BD-PSNR) of 0.1311% in low delay-P main profile. The performance comparison of test zonal search (TZS) along with MF-1BT is evaluated by comparing it with the TZS algorithm in the fast search mode of the HEVC encoder. Hexagon and diamond search algorithm along with MF-1BT is also proposed in the fast search mode of the HEVC encoder to further reduce the MET and ET compared with the TZS algorithm of the HEVC encoder.

Hardware Implementation of Diamond Search Algorithm for Motion Estimation

Motion estimation one of the advanced technique adapted in the industry for video coding and implemented in various applications. This work is focused on the efficient hardware implementation of the diamond search algorithm architecture. Among all the other Fast Search algorithms like three-step search, new three-step search, four-step search and diamond search (DS), the diamond search algorithm maintains the diamond shape search pattern and it gives faster search pattern and minimum absolute difference. When compared with the original diamond search (DS) algorithm, this modified diamond search algorithm requires less area and power maintaining the same performance. Other than the architectural level changes the low power synthesis is done and the results show that this design can be implemented effectively for an application that require fast search with low power requirements like IoT and sensor devices. The design has been implemented using Verilog HDL, synthesized using Synopsys DC compiler using 90nm technology.

Adaptive pattern selection strategy for diamond search algorithm in fast motion estimation

In this paper, an adaptive pattern selection strategy for diamond search (DS) algorithm is proposed. DS is one of state-of-the-art motion estimation algorithms, while the fixed search strategy and the singular termination strategy lead to lots of redundancy of search points. The proposed search strategy is based on the observation that more than 75% motion vector differences are around the initial predicted search centre in the range of 1. In our search strategy, small diamond search pattern and large diamond search pattern are adaptively used according to the distribution of motion vector differences and the matching error information of initial search centre. Our search strategy focuses on how to use small diamond search pattern and large diamond search pattern more efficiently than diamond search algorithm without introducing additional search patterns. Experimental results show that the proposed algorithm can save about 10.81 search points and achieve 0.12 dB higher PSNR on average compared to DS.

Object Detection and Tracking using Modified Diamond Search Block Matching Motion Estimation Algorithm

Object tracking is one of the main fields within computer vision. Amongst various methods/ approaches for object detection and tracking, the background subtraction approach makes the detection of object easier. To the detected object, apply the proposed block matching algorithm for generating the motion vectors. The existing diamond search (DS) and cross diamond search algorithms (CDS) are studied and experiments are carried out on various standard video data sets and user defined data sets. Based on the study and analysis of these two existing algorithms a modified diamond search pattern (MDS) algorithm is proposed using small diamond shape search pattern in initial step and large diamond shape (LDS) in further steps for motion estimation. The initial search pattern consists of five points in small diamond shape pattern and gradually grows into a large diamond shape pattern, based on the point with minimum cost function. The algorithm ends with the small shape pattern at last. The proposed MDS algorithm finds the smaller motion vectors and fewer searching points than the existing DS and CDS algorithms. Further, object detection is carried out by using background subtraction approach and finally, MDS motion estimation algorithm is used for tracking the object in color video sequences. The experiments are carried out by using different video data sets containing a single object. The results are evaluated and compared by using the evaluation parameters like average searching points per frame and average computational time per frame. The experimental results show that the MDS performs better than DS and CDS on average search point and average computation time.

A novel parallel implementation of partial distortion search algorithm based on template search

This paper proposes a new early terminating partial distortion search algorithm based on template search in fast motion estimation. Our algorithm accomplishes a parallel implementation technique by considering both the idea of partial distortion search and the advantage of the template search. With this technique, the proposed algorithm achieves a better performance by faster updating the current minimum distortion. The proposed parallel implementation that reduces a large amount of distortion computations between pixels outperforms the standard partial distortion search method by faster rejecting the unlikely candidate blocks. Our algorithm is embedded into the diamond search algorithm, star diamond search algorithm and three-step search algorithm respectively. According to the experiment results, it is proved that about 30% reduction of computational complexity has been obtained compared with the standard partial distortion search. Moreover, there is no degradation of the peak signal-to-noise ratio(PSNR) for motion estimation compared with the embedded block-based template search motion estimation algorithm.

Performance analysis of diamond search algorithm over full search algorithm

Motion estimation is a progression used to estimate motion vectors between two or more images with a high degree of temporal redundancy. It is commonly used in video compression to attain high compression ratios as well as used in several applications for object tracking. In this paper a novel approach for diamond search algorithm has been recommended to overcome the problem encountered by several existing block matching algorithms especially with full search algorithm in reference of peak signal-to-noise ratio, required number of examine or search points as well as computational complexity. Simulation results reflect that recommended algorithm acting well compared to all existing algorithms. Experimentally 88–99% of the motion vectors are found inside the circle which has radius of 3-pixel unit and fixed on the place of zero motion. The proposed algorithm is used to implement various standards examples such as MPEG1 and MPEG4.

Real-time motion estimation diamond search algorithm for the new high efficiency video coding on FPGA

High efficiency video coding (HEVC) is the latest video coding standard aimed to replace the H.264/AVC standard according to its high coding performance, which allows it to be mostly suitable for application in high definition videos. However, this performance is accompanied by a high computational complexity due principally to the motion estimation (ME) algorithm. As in H.264/AVC, the ME in HEVC is a highly computational demanding part that takes the largest part of the whole encoding time. Hence, many fast algorithms have been proposed in order to reduce computation, but, the majority, do not study how they can be effectively implemented by hardware. In this paper, two hardware architectures of the diamond pattern search algorithm for HEVC video coding with sequential and parallel techniques, are proposed. These architectures are based on parallel processing techniques. The sequential and parallel VHDL codes have been verified and can achieve at a high frequency on a Virtex-7 field-programmable gate-array design (FPGA) circuit. Compared to other designs, our parallel design provides better efficient implementation of available resources on FPGA. Our architecture can meet the real-time processing of the FHD @ 30 frames per second.

Fast Motion Estimation Algorithm using Hybrid Search Patterns for Video Streaming Application

The objective of the paper is to develop new block matching Motion Estimation (ME) algorithm using hybrid search patterns along the direction of best match. The search efficiency for sequences with fast motions and high resolutions is improved by proposing New Cross Diagonal-Hexagon Search (NCDHS) algorithm which involves a novel multi half-hexagon grid global search pattern and a cross diagonal-hexagon local search pattern. The new search pattern enables the proposed algorithm to perform better search using 9.068 search points on an average, to obtain optimal motion vector with slight improvement in quality. This inturn reduces ME Time upto 50.11%, 47.12%, 32.99% and 43.28% on average when compared to the existing Diamond Search (DS), Hexagon Search (HS), New Cross Hexagon Search (NHEXS) and Enhanced Diamond Search (EDS) algorithms respectively. The novelty of the algorithm is further achieved by applying the algorithm proposed for live streaming application. The NCDHS algorithm is run on two MATLAB sessions on the same computer by establishing the connection using Transmission Control Protocol (TCP) /Internet Protocol (IP) network. The ME Time obtained is 14.5986 seconds for a block size 16x16, is less when compared to existing algorithms and that makes the NCDHS algorithm suitable for real time streaming application.

Biblographic Survey and Comparison Of Different Block Matching Algorithms

In communication world dealing with transfer and reception of digital video, practically, it is not possible to store the full moving image sequence because of the problems that encountered during its storage and transmission. Due to this reason, video compression is essentially required. The basic idea behind the compression technology is to remove the redundant data from the video file so that it can be transmitted over the network line using less number of bits and can be effectively stored on system disks. For video compression, motion estimation is the key element for finding the motion between successive frames and is achieved using block matching algorithm. In this paper, literature survey of block based motion estimation algorithms is carried out. It compares five basic block matching based motion estimation algorithms namely exhaustive search (ES), three step search (TSS), new three step search (NTSS), four step search (FSS) and diamond search (DS) algorithm on the basis of number of search location and their advantages and disadvantages. The algorithms concluded in this paper are used for various standards.

Super resolution and recognition of long range captured multi‐frame iris images

In this study, a framework to super resolve and recognise the long range captured iris polar images is proposed. The proposed framework consists of best frame selection algorithm, modified diamond search algorithm, Gaussian process regression (GPR) based and enhanced iterated back projection (EIBP)-based super-resolution approach, fuzzy entropy-based feature selector and neural network (NN) classifier. The framework uses linear kernel co-variance function in local patch-based GPR and EIBP algorithms and it super resolves the iris images depending on the contents of the patches, without an external dataset. NN classifier classifies the iris images by using features extracted using discrete cosine transform domain based no-reference image quality assessment model, Gray level co-occurrence matrix, Hu seven moments and statistical features. The framework is tested using CASIA long range iris database by comparing and analysing the peak signal-to-noise ratio, structural similarity index matrix and visual information fidelity in pixel domain of proposed algorithms with Yang and Nguyen framework. The results demonstrate that the proposed framework is well suited for recognition of iris images captured at a long distance.

AN EFFICIENT BLOCK MATCHING ALGORITHM FOR FAST MOTION ESTIMATION USING COMBINED THREE STEP SEARCH AND DIAMOND SEARCH ALGORITHM

Recent day Communication between ends is facilitated by the development in the area of wired and wireless networks. So many researches are going on the field of motion estimation to achieve the requirement of recent day technology. Block matching algorithms are very useful in achieving the efficient and acceptable motion estimation. Total computation cost and bit budgeting can be efficiently controlled by properly modifying block matching algorithms. Video coding using Orthogonal Logarithmic Search Algorithm (OSA) is one of the best block matching algorithms used now days. Motion estimation is the most time consuming operation in a typical video encoder. This paper presents a novel method by combining modified three step (M3SS) algorithm with a different search pattern and diamond search (DS) based on dead cell for the block based motion estimation. Result shows that from the original Three step Search (3SS/TSS ) method, the PSNR value has increased and the computations time has been reduced effectively by modified 3SS and again to increase the search space we combined diamond search(DS) algorithm. The experimental results based on different video frames were compared to demonstrate the advantages of proposed fast motion estimation algorithm.