Mohamed M. Rehan

An FPGA implementation of the flexible triangle search algorithm for block based motion estimation

In this paper a hardware architecture for the implementation of the flexible triangle search algorithm (FTS) using FPGAs is proposed. The FTS is a fast block-matching algorithm for motion estimation proposed in previous work, which can be used for video compression. The FTS finds the best matching blocks between two frames using a search triangle which changes its direction and size through a set of operations. These operations provide the triangle with the necessary flexibility to locate the best matching block. Simulation results indicate that the FTS reduces the number of block matching operations compared with other fast block matching algorithms without affecting quality or compression ratio of the compressed bitstream. In this paper, a hardware architecture for a FPGA implementation of the FTS algorithm is proposed. This architecture is simulated and tested using VHDL and synthesized using Xilinx ISE for the Xilinx Spartan3 device. The results obtained were compared to an FPGA implementation of the full search (FS) algorithm. Results indicates that the FTS FPGA implementation requires less number of gates than FS and the required number of cycles needed to complete motion search for one block is much lower. This indicates that the proposed implementation is fast and requires less hardware and power than existing ones

Flexible triangle search algorithm for block based motion estimation

A new fast algorithm for block-based motion estimation, the flexible triangle search (FTS) algorithm, is presented. The algorithm is based on the simplex method of optimization adapted to an integer grid. The proposed algorithm is highly flexible due to its ability to quickly change its search direction and to move towards the target of the search criterion. It is also capable of increasing or decreasing its search step size to allow coarser or finer search. Unlike other fast search algorithms, the FTS can escape from inferior local minima and thus converge to better solutions. The FTS was implemented as part of the H.264 encoder and was compared with several other block matching algorithms. The results obtained show that the FTS can reduce the number of block matching comparisons by around 30–60% with negligible effect on the image quality and compression ratio.

Block-based motion estimation using an enhanced flexible triangle search algorithm

A fast algorithm for block-based motion estimation, the enhanced flexible triangle search (EFTS) algorithm, is presented. This algorithm is based on the general idea of the simplex algorithm and is an enhanced and improved version of the flexible triangle search (FTS) algorithm proposed recently by the authors. The EFTS algorithm was implemented as part of an H.263 encoder and was compared with commonly used block-based motion estimation algorithms. The results obtained indicate that the EFTS reduces significantly the number of matching criterion evaluations per macroblock than all other techniques without any deterioration in the visual quality of the reconstructed video sequence or in the compression ratio

A new fast block matching algorithm using the simplex technique

A new fast technique for block-based motion estimation using the simplex technique is presented. Block-based motion estimation is used in several video compression applications and standards. The simplex search is a fast search technique that converges rapidly towards the minimum point in small or irregular search areas. It starts with a certain initial-point configuration and then moves towards the solution through a set of operations. These operations include reflection, expansion, and contraction. The proposed technique was implemented as part of the MPEG-2 encoder and was compared with different search techniques. The results obtained show that the technique has better performance over some existing techniques in terms of computation complexity and motion estimation accuracy.

A new motion-estimation technique for efficient video compression

A new prediction technique for block-based motion estimation (ME) is described. The new technique, referred to as weighted sum block matching (WSBM), changes different motion estimation parameters such as the search window origin and the search window size based on prediction information which is extracted from motion information of neighboring blocks. The new technique was used for ME in the MPEG-2 encoder and was compared with different other block matching algorithms (BMAs). Simulation results show that the new technique provides less block matching computation over other prediction techniques. Moreover, the new technique can be combined with different non-predictive techniques to improve their performance.

Prediction-Based Flexible Triangle Search Algorithm for Block Based Motion Estimation

This paper presents a technique that predicts the initial search direction for the flexible triangle search algorithm (FTS), which was introduced in previous work by the authors. The FTS algorithm is a fast block-matching algorithm for block-based motion estimation. In the FTS, a search triangle is used to find the best matching blocks between two frames through successive iterations. During the search, the triangle changes its direction and size using reflection, expansion, contraction, and translation operations. These operations provide the triangle with the necessary flexibility to perform coarse or fine search and to locate the best matching blocks while checking fewer search positions compared to most other search algorithms. Analysis of the FTS behavior showed that the proper selection of the starting triangle for the search reduces the required number of block-matching evaluations by directing the search earlier in the direction of the minimum. In this paper, a prediction-based FTS, the PFTS, is introduced. In the PFTS, a prediction step is added to obtain the initial triangle for the search. Simulation results indicate that the PFTS requires a smaller number of block matching operations than that of the FTS. In addition, the compression ratio was improved slightly while the visual quality of the reconstructed sequence remained the same compared to the FTS

Half-pixel accurate motion-estimation using a flexible triangle search

In this paper, a technique for half-pixel motion estimation using the flexible triangle search (FTS) algorithm is presented. The FTS algorithm is based on the simplex algorithm and has been presented and analyzed in previous work by authors. The approach proposed in this paper for half-pixel motion estimation is based on combining full- pixel and half-pixel searches into a single stage instead of using two separate search stages as commonly used. The resulting half-pixel FTS, HP-FTS, is implemented and analyzed as part of an H.263 encoder. Results indicate that the computational complexity of the proposed HP-FTS is lower compared to a two-stage (full-pixel first and half-pixel second) FTS algorithm. Further, the compression ratios and the quality of the reconstructed sequences using the proposed HP-FTS are similar to those of the two-stage FTS.

Partially blurred images restoration using adaptive multi-stage approach

This paper presents an efficient image restoration algorithm that is content adaptive. Traditional image restoration or de-blurring algorithms apply the same logic on the whole image even when only few image blocks are blurry. The developed algorithm is designed to use less calculations and save the un-blurred image parts quality during the de-blurring process. When more than one image is used, our algorithm is designed to select the best extracted quality from each image on a block bases. Our proposed approach consists of three main stages. In the first stage, the detection of blurry blocks of an image is performed. In the second stage, a partial de-blurring is applied only to the detected blurry blocks. In the third stage, an image fusion technique is used to fuse the de-blurred blocks back into the final image to be restored. MATLAB was used for our simulation results. Simulation results using various evaluation metrics showed that our proposed approach has achieved up to 14 dB (36%) enhancement based on PSNR for partially blurred images where blurry blocks are not in the same spatial position in the input images and close to 1 dB in cases where the blurry blocks are in the same spatial position.

Dynamic peer-assisted DASH framework using dynamic updates and prioritization scheme

In this paper, we present a dynamic framework for P2P video streaming using dynamic adaptive streaming over HTTP (DASH). DASH is a very popular standard and is expected to dominate the adaptive streaming market. Our proposed framework defines several components; DASH Session Coordinator (DSC), Intelligent Content Server (ICS), and Adaptive Streaming Client (ASC). Each component has a defined set of rules as well as a simple messaging framework. In addition, all components work together to achieve optimized QoE for all clients streaming the same content. The proposed framework is customized for DASH and provides higher priority for P2P streaming over direct streaming thus allowing clients to share downloading content instead of competing for higher bandwidth and consequently improve network utilization and client QoE. Results of our proposed technique showed an increase in client download rate by approximately 60% which is directly related to the QoE perceived by the client. In addition, a reduction of 87% in the number of playback stalls and pauses was achieved due to the elimination of bandwidth competition among clients.