Near-lossless compression for high frame rate videos

Abstract

The widespread usage of internet, limited bandwidth of networks and different types of media all around the net causes a vast growth in compressing data with different abilities and qualities. Nowadays, video is a popular media for everyday usage. In different research areas, there is a need for recording events in high frame rates. Due to the high frame rate video constraints, using complex methods are not suitable for real-time coding of these videos and will increase the cost of the system. There are different lossless, lossy and near-lossless methods for compressing video sequences. Existing lossy methods cannot limit the subjective or objective loss to a certain upper bound. There have been works regarding lossless compression of these sequences, however these works offer modest compression ratios and in some cases will not be enough due to the large size of these sequences. In this paper we propose a near-lossless method that is comparable with successful existing methods of video compression and yet is simple enough for real-time applications. It includes the major conventional parts for this goal which are prediction, quantization and entropy coding. A simple rate control is embedded by different approaches in quantization. The experimental results demonstrate good compression ratios while considering reliability due to control of the maximum pixel error.

A Novel Medical Image Compression Technique based on Structure Reference Selection using Integer Wavelet Transform Function and PSO Algorithm

“…Hybrid image compression incorporates diverse compression systems like PVQ and DCTVQ in a single image compression. Image compression is a process of efficiently coding of digital image, to reduce the number of bits required in representing image [12,13]. Its purpose is to reduce the storage space and transmission cost while maintaining good quality.…”