Abstract

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.

Highlights

  • Video compression techniques deal with the lossy or lossless data compression for the series of image sequences

  • Standard input streams with different frame rates, lengths of sequences, and frame widths/heights were considered to demonstrate the performance of the proposed approach

  • In Block matching algorithms, the size of macro block is the important parameter for motion estimation

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Summary

Introduction

Video compression techniques deal with the lossy or lossless data compression for the series of image sequences. Block matching motion estimation plays an important role in interframe coding technique to reduce temporal redundancy present in the series of image sequences. It is a most popular and efficient technique for computing the motion vectors which has been used by various coding standards. This paper discusses a modified three step search algorithm for block matching motion estimation and WFA coding approach for color video compression.

Three Step Search Algorithm
New Cross Hexagonal Search Algorithm
Proposed Approach
Weighted Finite Automata Representation
Experimental Results and Discussion
Quality Measures
Evaluation and Comparison of Fractal Coding
Conclusion and Future Scope
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