Hexagonal Search Research Articles

An Improved Fast Motion Estimation Algorithm in H.266/VVC

Motion estimation is a key technique of video compression coding, H.266/VVC (Versatile Video Coding) inter TZsearch fast motion estimation algorithm using the diamond search model, although the search model matching precision is high, but because of the number of search points need to match, so the computational complexity is higher also, for this defect, the article on the basis of the standard algorithm, The fast algorithm of TZSearch is optimized and improved. Firstly, the hexagonal search model with excellent performance and speed is used to replace the diamond search model in the standard algorithm. Secondly, on the basis of the rotation hexagon model, the number of initial matching search points of the rotation hexagon search model is further increased by using the feature of natural video prediction MV center bias. At the same time, a reasonable early termination threshold is set for the whole motion estimation process. Simulation results show that compared with VTM14.0 standard algorithm, the proposed algorithm reduces BDBR by 0.17% and BDPSNR by 0.04dB on average, and the overall coding time is saved by 48.85% on average. The proposed algorithm can effectively reduce the computational complexity of motion estimation process on the premise of guaranteeing the coding quality.

A Motion Estimation based Algorithm for Encoding Time Reduction in HEVC


 
 
 High Efficiency Video Coding (HEVC) is a video compression standard that offers 50% more efficiency at the expense of high encoding time contrasted with the H.264 Advanced Video Coding (AVC) standard. The encoding time must be reduced to satisfy the needs of real-time applications. This paper has proposed the Multi- Level Resolution Vertical Subsampling (MLRVS) algorithm to reduce the encoding time. The vertical subsampling minimizes the number of Sum of Absolute Difference (SAD) computations during the motion estimation process. The complexity reduction algorithm is also used for fast coding the coefficients of the quantised block using a flag decision. Two distinct search patterns are suggested: New Cross Diamond Diamond (NCDD) and New Cross Diamond Hexagonal (NCDH) search patterns, which reduce the time needed to locate the motion vectors. In this paper, the MLRVS algorithm with NCDD and MLRVS algorithm with NCDH search patterns are simulated separately and analyzed. The results show that the encoding time of the encoder is decreased by 55% with MLRVS algorithm using NCDD search pattern and 56% with MLRVS using NCDH search pattern compared to HM16.5 with Test Zone (TZ) search algorithm. These results are achieved with a slight increase in bit rate and negligible deterioration in output video quality.
 
 

Motion Estimation for Gray Level Videos Using Different Block Matching Algorithms

Motion Estimation (ME) is a very important operation in video coding. In order to reduce complexity of computations involved in ME and to increase quality of this process, many Block Matching Motion Estimation (BMME) Algorithms are proposed. The aim of this paper is to compare between these algorithms and find the best one. Seven BMME algorithms are used in this paper. The performance of each algorithm is evaluated for different types of motion to determine the best one of these algorithms. The evaluation is based on search points, and Peak Signal to Noise Ratio (PSNR). The simulation shows that Hexagonal Search is faster than all other Block Matching (BM) algorithms used in this paper regardless the type of video because it requires less number of search points to evaluate motion vectors for the video sequence. It requires 11.2424 average search point (SP) for small motions and 13.9708 for fast motions. It also gives a good quality that is close enough to the quality given by Full Search

A Novel Kite Cross Hexagonal Search Algorithm for Fast Block Motion Estimation

The performance quality and searching speed of Block Matching (BM) algorithm are affected by shapes and sizes of the search patterns used in the algorithm. In this paper, Kite Cross Hexagonal Search (KCHS) is proposed. This algorithm uses different search patterns (kite, cross, and hexagonal) to search for the best Motion Vector (MV). In first step, KCHS uses cross search pattern. In second step, it uses one of kite search patterns (up, down, left, or right depending on the first step). In subsequent steps, it uses large/small Hexagonal Search (HS) patterns. This new algorithm is compared with several known fast block matching algorithms. Comparisons are based on search points and Peak Signal to Noise Ratio (PSNR). According to results obtained in this paper, KCHS needs less search time than others algorithms and gives very acceptable performance quality.

Video compression using hybrid hexagon search and teaching–learning-based optimization technique for 3D reconstruction

Motion estimation from a video sequence is an interesting issue in video processing. Nowadays, research has been focused on global optimization techniques, that estimate the optical flow for pixel neighborhoods. In this paper, a hybrid statistically effective motion estimation procedure has been proposed for better effectiveness video compression. This method explores by utilizing a hexagonal search pattern with a secure number of search points at every lattice. It uses the association among bordering pixels within the frame. So as to diminish the computative intricacy, this methodology uses hybrid hexagon search and teaching–learning based optimization algorithm. This method additionally decreases the computational unpredictability of block matching procedure. The image quality has been confirmed through 3D reconstruction using structured light techniques. This strategy has been contrasted with different existing strategies and hereby utilizing the hexagon search-based teaching–learning optimization algorithm could get a higher precision interms of PSNR of 44.36%, MSE of 2.40 and compression ratio of 7.50.

Improved motion estimation algorithm based on integrity index and its implementation in x265

With the development of fast motion estimation (ME) algorithms towards video compression standard H.264, burden on integer-pel ME is slightly reduced. However the integer-pel ME is becoming computationally complex due to demand of higher and higher resolution videos. On the other hand, there is always trade-off between the speed and performance of these search algorithms. This work improvises the performance of content awareness enabled integer-pel ME algorithm for encoding the fast and slow motion video sequences of high definition (HD) resolution category viz. 1280×720 and 1920×1080. The algorithm proposes a novel notion of 'integrity index' with focus on increasing the PSNR and reducing the bit rate. It is implemented in the frame work of x265 version 1.7 video encoder. Motion independent ME algorithm is analysed quantitatively in terms of parameters based on rate distortion and ME time. The proposed algorithm is found to be performing better on BD-Rate and BD-PSNR parameters for the videos of both resolutions under consideration. Observed increase in motion estimation time is less than four seconds compared to hexagonal search algorithm of ME which is the benchmark in fast ME algorithm.

Multi‐objective genetic algorithm on hexagonal search for fast motion estimation

Motion estimation (ME) is a process of correlating the frames by pointing the blocks in the candidate frame similar to those in the previous frame. Hexagonal Search (HS) reduces 10–15% search points over Diamond Search (DS) with negligible Peak Signal to Noise Ratio (PSNR) loss. Adapting an optimization will achieve a massive improvement on the search process. The proposed HS-GA method combines the HS with genetic algorithm (GA) to optimize ME. The HS-GA method reduces 72% on average search points pre block (ASPB) with PSNR loss of 2.5 dB and single generation. If the GA is executed with 10 generations the PSNR loss is reduced to 0.48 dB, but ASPB drastically increase to ∼316%. The proposed work aims at multi objective on selection of better chromosomes and on control of generations to avoid the unnecessary generations to improve the GA. This process is named HSIGA(HS with Intelligent GA). The proposed HSIGA adapts five intelligent techniques like Histogram to decide new generations, Region based chromosome selection, Mutation on inner search gene, second rank valley point stopping criteria and interlaced HS to improve search process with negligible PSNR loss with in affordable search.

Optimized Hexagonal Search for Fast Motion Estimation Based on Bees Algorithm

Optimized Hexagonal Search for Fast Motion Estimation Based on Bees Algorithm

A novel diamond–hexagon search algorithm for motion estimation

Motion estimation (ME) is initial way for video compression and associated to the compression efficacy by dipping temporal redundancies. ME is the most significant measure of a video encoder and half of coding intricacy or computational time depends on it. There were numerous ME algorithms suggested and realized to minimalize the computational time. H.264/AVC codec deals various coding method for realizing high compression gains as relate to other criterions. These methods affectedly rise the computational intricacy of the block based ME, which consumes up to 80% of the complete encoder’s computations. In this paper, we proposed diamond–hexagon search algorithm for block matching ME method. This proposed method delivers lessening in computational intricacy and encoding time without conceding the quality of the video sequence.

Accelerating motion estimation by genetic algorithm approach in x265

In the last two decades, in the domain of video coding and compression, researchers have suggested several techniques for computation and time reduction for motion estimation (ME). We present a motion estimation algorithm for x265 video codec, based on a deterministic initial population in the genetic algorithm (GA). GA is known for its adaptive convergence, which is motivated by the biological process of survival of the fittest. The suggested scheme is targeted for the reduction of search points (SP) in a block matching motion estimation algorithm for integer-pel in B and P frames that are set to have three reference frames. The initial population constituted in our approach is a function of pre-encoded coding units at different spatial–temporal locations of the video frames and predefined hexagonal (HEX) locations. We propose a “deterministically starting” GA (GADet), toward deployment in x256 structure. In the framework of x265 code, GADet is found to offer reduction in SP at selected classes of videos considered for experimentation. To demonstrate the effectiveness of the proposed work, results have been compared with the block-based fast-full-search algorithm and the HEX search algorithm from the reference software. Traditional GA with a randomly constituted initial population, labeled as GAStc, is also implemented and an empirical comparison is carried out with GADet. The proposed GADet framework provides reduction in motion estimation time while rendering acceptable peak signal-to-noise ratio loss and an increase in a bit rate.

Adaptive Order Cross–Square–Hexagonal search and fuzzy tangential-weighted trade-off for H.264 in motion estimation

In recent years, various algorithms have been proposed to attain low computational complexity in motion estimation of the image sequence coding based on block matching. This paper presents an Adaptive Order Cross–Square–Hexagon (AOCSH) search algorithm, which employs a smaller cross-shaped pattern before the first step of a square pattern and replaces the square-shaped pattern with the hexagon search patterns in subsequent steps. The proposed search patterns aid in finding the best matching block, without much consideration of the vast number of search points. Here, fuzzy tangent-weighted function is also proposed to evaluate the matching points using the rate and the distortion parameters. The proposed methods are effectively applied to the block estimation process to handle the objectives of visual quality and distortion. The performance of the proposed AOCSH approach is compared to the existing methods, such as AOSH, H.264 and elastic models, using the structural similarity index (SSIM) and the peak signal to noise ratio (PSNR). From the analysis, it can be seen that the proposed approach attains the maximum SSIM of 0.99 and maximum PSNR of 40. 92 dB with reduced computation time of 3.28 s.

Hybrid Motion Estimation Algorithm Based on PSO with Dynamic Threshold on Static Block Detection

Motion Estimation(ME) technology is a platform in Video compression technology and so it is most complex process in video encoder. The challenge in the ME is to detect the best Motion Vector (MV) in less number of search points in the search plane. Pattern oriented search provides significant reduction on search points, especially the Hexagonal Search(HS) is much better, but last two decades the video codec’s demands acceleration on ME process to lighter encoder to adapt for even small scale hard cores. So there is necessary of optimization on search process. The proposed work optimize the ME process based on Particle Swarm Optimization PSO, and to improve performance of PSO its hybrid with HS. Also in this paper a method is proposed to detect the static blocks in image sequence by dynamic threshold. The PSNR and average search points per block are two metrics to measure the performance and its compared with popular search pattern techniques. The hybrid technique reduce the search points to 70% with the PSNR loss of 0.8dB. This method could be adapted to any video codec, to speed its ME process.

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.

Enhanced dynamic pattern search algorithm with weighted search points for fast motion estimation

For video encoding, a number of block-based motion estimation techniques have been proposed in the literature. Some of them are based on fixed search patterns, whereas others are utilizing spatial and temporal correlations of blocks within video frames. It has been found that the block correlations give an initial lead in identification of motion vector of the candidate block and the possibility of oversearch or undersearch is minimized. In this paper, the dynamic pattern search (DPS) algorithm for block-based motion estimation has been enhanced which reduces the search point computation by first identifying the stationary blocks. Further, in the proposed algorithm, search points within the search area are evaluated for minimum distortion point in prioritized fashion to reduce the possibility of being trapped in local minima. The proposed work has been compared experimentally with fixed search pattern techniques like full search, diamond search (DS) and hexagon search and adaptive search pattern techniques like adaptive rood pattern search and DPS in terms of various performance parameters. It has been found that the proposed technique is faster by 6.32 and 3.30 times than DS and DPS techniques in terms of avg. search point computation per block and produces better peak signal to noise ratio than DS and DPS by the value of 1.03 and 0.63 dB, respectively. In terms of structural similarity measurement index value, enhanced DPS gives 8% better results than DPS and performs better compression than any other technique except FS.

An improved adaptive selection search for block motion estimation

Motion estimation has an important effect in H.265 video coding systems because it occupies a large amount of time in encoding system. So the quality of motion search selection affects the entire encoding efficiency directly. In this paper, a novel search algorithm which utilises an adaptive hexagon and small diamond search is proposed to overcome the drawbacks of the traditional block matching selection implemented in most current video coding standards. The adaptive search algorithm is chosen according to the motion strength of the current block. When the block is in active motion, the hexagon search provides an efficient search method; when the block is inactive, the small diamond search is adopted. Experimental simulation results showed that our adaptive search algorithm can speed up the search process with little effect on distortion performance compared with other traditional approaches.

An improved adaptive selection search for block motion estimation

Motion estimation has an important effect in H.265 video coding systems because it occupies a large amount of time in encoding system. So the quality of motion search selection affects the entire encoding efficiency directly. In this paper, a novel search algorithm which utilises an adaptive hexagon and small diamond search is proposed to overcome the drawbacks of the traditional block matching selection implemented in most current video coding standards. The adaptive search algorithm is chosen according to the motion strength of the current block. When the block is in active motion, the hexagon search provides an efficient search method; when the block is inactive, the small diamond search is adopted. Experimental simulation results showed that our adaptive search algorithm can speed up the search process with little effect on distortion performance compared with other traditional approaches.

Modified Three-Step Search Block Matching Motion Estimation and Weighted Finite Automata based Fractal Video Compression

The major challenge with fractal image/video coding technique is that, it requires more encoding time. Therefore, how to reduce the encoding time is the research component remains in the fractal coding. Block matching motion estimation algorithms are used, to reduce the computations performed in the process of encoding. The objective of the proposed work is to develop an approach for video coding using modified three step search (MTSS) block matching algorithm and weighted finite automata (WFA) coding with a specific focus on reducing the encoding time. The MTSS block matching algorithm are used for computing motion vectors between the two frames i.e. displacement of pixels and WFA is used for the coding as it behaves like the Fractal Coding (FC). WFA represents an image (frame or motion compensated prediction error) based on the idea of fractal that the image has self-similarity in itself. The self-similarity is sought from the symmetry of an image, so the encoding algorithm divides an image into multi-levels of quad-tree segmentations and creates an automaton from the sub-images. The proposed MTSS block matching algorithm is based on the combination of rectangular and hexagonal search pattern and compared with the existing New Three-Step Search (NTSS), Three-Step Search (TSS), and Efficient Three-Step Search (ETSS) block matching estimation algorithm. The performance of the proposed MTSS block matching algorithm is evaluated on the basis of performance evaluation parameters i.e. mean absolute difference (MAD) and average search points required per frame. Mean of absolute difference (MAD) distortion function is used as the block distortion measure (BDM). Finally, developed approaches namely, MTSS and WFA, MTSS and FC, and Plane FC (applied on every frame) are compared with each other. The experimentations are carried out on the standard uncompressed video databases, namely, akiyo, bus, mobile, suzie, traffic, football, soccer, ice etc. Developed approaches are compared on the basis of performance evaluation parameters, namely, encoding time, decoding time, compression ratio and Peak Signal to Noise Ratio (PSNR). The video compression using MTSS and WFA coding performs better than MTSS and fractal coding, and frame by frame fractal coding in terms of achieving reduced encoding time and better quality of video.

Adaptive order search and tangent-weighted trade-off for motion estimation in H.264

Motion estimation and compensation play a major role in video compression to reduce the temporal redundancies of the input videos. A variety of block search patterns have been developed for matching the blocks with reduced computational complexity, without affecting the visual quality. In this paper, block motion estimation is achieved through integrating the square as well as the hexagonal search patterns with adaptive order. The proposed algorithm is called, AOSH (Adaptive Order Square Hexagonal Search) algorithm, and it finds the best matching block with a reduced number of search points. The searching function is formulated as a trade-off criterion here. Hence, the tangent-weighted function is newly developed to evaluate the matching point. The proposed AOSH search algorithm and the tangent-weighted trade-off criterion are effectively applied to the block estimation process to enhance the visual quality and the compression performance. The proposed method is validated using three videos namely, football, garden and tennis. The quantitative performance of the proposed method and the existing methods is analysed using the Structural SImilarity Index (SSIM) and the Peak Signal to Noise Ratio (PSNR). The results prove that the proposed method offers good visual quality than the existing methods.

Intra-hour cloud movement detection for solar forecasts based on ground imaging system

The penetration of solar energy continues to rise and becomes a central piece of the global energy mix. Thus, considering ways for more efficiently operated power systems to accommodate significant amounts of such a variable resource will be increasingly important. Improvements in solar forecasting methods and techniques will clearly be relevant. In addition to season and irradiation angle, the most important factor of influencing solar energy output is the effect of cloud movement on solar irradiation shadow on solar plate. This paper briefly analyzes the advantages and disadvantages of various moving target algorithms, and compares the typical feature matching algorithm (block motion estimation algorithm) and optical flow algorithm (CLG algorithm) against the collected cloud movement image sequence. The result shows that optical flow algorithm (CLG algorithm) is applied to cloud movement image. The calculation is very fast, with an accuracy above 96%. A comparison with CLG algorithm shows that direction and speed accuracy of block motion estimation algorithm based on hexagonal search pattern is 0.79 and 0.47, respectively.

Speed-Area Optimized VLSI Architecture of Hexagonal Search Algorithm for Motion Estimation of $$512 \times 512$$ 512 × 512 Frames

Motion estimation accounts for major part of the computational complexity of any video coding standard. In this paper, we present efficient VLSI architecture for the implementation of hexagonal search algorithm for fast motion estimation. The proposed architecture employs sequential processing of pixel data rather than parallel processing in order to reduce the hardware area substantially while achieving the real-time speed. A novel on-chip memory organization is proposed, which reduces the address generation complexity and helps improve the speed. The architecture when implemented in Verilog HDL and mapped to Virtex-5 FPGA achieves a maximum frequency of 340 MHz, while the gate count is calculated to be 3.1 K. Thus, the proposed architecture is considered suitable to be incorporated in commercial devices such as camcorders and smart phones.