Abstract
Video compression ratio, quality and efficiency are determined by the motion estimation algorithm. Motion estimation is used to perform inter frame prediction in video sequences. The individual frames are divided into blocks the motion estimation is computed by a video codec such as H.264. A video codec computes the displacement of block between the previous frame (reference frame) and the current frame, for each block in current frame the best motion vector is determined in the reference frame as a block belongs to a current frame. In this, research paper, a novel technique has been presented for motion vector calculation, using fuzzy Gaussian membership function. The motion estimation block uses fuzzy membership function to estimate the connectedness of different blocks of the current frame to that of the reference frame The fuzzy decision matching is done based on the matching criterion and the best matching block is selected. The motion vectors are thus calculated with respect to the reference frame. The fuzzification process produces optimally matched blocks, which are then utilized to calculate the motion vectors of the predicted frame. Using fuzzy based search the search area is automatically updated and adaptive search steps provides an optimized result of search. As in real time streaming no file is exchanged during the transmission user is not able to download the file the only way for smooth transmission is frame management fuzzy based search for the motion estimation provides a better compression for the predicted frames.
Highlights
High resolution images and videos have been made accessible to everyone by the use of the technology
The experiment leads to decreased video quality variability in contrast with the current approaches and increased 40% of bandwidth consumption
Unlike the other algorithm here the Sum of Absolute Differences (SAD) is calculated by the Gaussian membership function (GMF) which is assigned for macroblock for previous frame and the macroblocks of target frame for each pixel and a membership data matrix is created
Summary
High resolution images and videos have been made accessible to everyone by the use of the technology. Image frames need to be stored and transmitted in time and space using broadband transmission This includes a modern video encoding format to safely and share video data in real time. Two main motion vector estimation techniques currently are available pel-recursive algorithm and the block matching algorithm. Each picture is divided into a fixed size that does not overlap rectangular blocks of either current or reference frames in the corresponding block algorithms These blocks are matched, based on some cost function, to find the best matching block, for which motion vectors are calculated. Several algorithms for fast search and real time deployment were proposed to resolve the limitations of the complete search algorithm Some of these algorithms look for the matching block only in a set of blocks in the search area. Spatio-temporal fuzzy search algorithm using a look-up table structure (LUT) is employed [5]
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