Abstract

In image compression and video coding, quantization error helps to reduce the amount of information of the high frequency components. However, in temporal prediction the quantization error contributes its value as noise in the total residual information. Therefore, the residual signal of the inter

Highlights

  • The growth of Internet of Things (IoT) in industry has been garnering substantial momentum in the last few years

  • Comparing to the conventional Hybrid (DPCM) video coding scheme, the coding time and bitrate of this scheme depend on three more factors: the complexity of motion detection algorithm, block based filters, and static percentage

  • The paper presented how the quantization error affects on stationary blocks

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Summary

Introduction

The growth of Internet of Things (IoT) in industry has been garnering substantial momentum in the last few years. Compared to other video codecs, MJPEG requires a minimum hardware resource and is strongly recommended for limited systems Another advantage is that it is only based on JPEG standard, it is widely supported and can be setup. H.265/HEVC is the successor of H.264/AVC video codec standard It achieves twice compression ratio as much as H.264/AVC [5] but requires more power full system to be implemented. HEVC standard is designed for high resolution video, up to 8192 × 4320 (8K UltraHigh-Definition (UHD)) At this moment, embedding HEVC into surveillance camera systems is quite limited because of the hardware constraints. Including quantization errors in residual information of static part decreases the compression ratio and the quality of the inter frame and increases the Entropy coding time.

Effect of Quantization Error in Inter Frame
Avoiding Quantization Error in Static
A Simple Motion Detection Algorithm
Block based Filter for Motion Detection Algorithm
Experience of the Proposed Video Encoding Architecture with JPEG Standard
Findings
Conclusion
Full Text
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