Abstract

Video applications have become one of the major services in the engineering field, which are implemented by server–client systems connected via the Internet, broadcasting services for mobile devices such as smartphones and surveillance cameras for security. Recently, the majority of video encoding mechanisms to reduce the data rate are mainly lossy compression methods such as the MPEG format. However, when we consider special needs for high-speed communication such as display applications and object detection ones with high accuracy from the video stream, we need to address the encoding mechanism without any loss of pixel information, called visually lossless compression. This paper focuses on the Adaptive Differential Pulse Code Modulation (ADPCM) that encodes a data stream into a constant bit length per data element. However, the conventional ADPCM does not have any mechanism to control dynamically the encoding bit length. We propose a novel ADPCM that provides a mechanism with a variable bit-length control, called ADPCM-VBL, for the encoding/decoding mechanism. Furthermore, since we expect that the encoded data from ADPCM maintains low entropy, we expect to reduce the amount of data by applying a lossless data compression. Applying ADPCM-VBL and a lossless data compression, this paper proposes a video transfer system that controls throughput autonomously in the communication data path. Through evaluations focusing on the aspects of the encoding performance and the image quality, we confirm that the proposed mechanisms effectively work on the applications that needs visually lossless compression by encoding video stream in low latency.

Highlights

  • The video data stream is one of main data streams utilized in the recent mobile and Internet of Things (IoT) applications

  • We evaluated the compression ratios derived from Adaptive Stream-based Entropy (ASE) coding where the encoded data stream generated by Adaptive Differential Pulse Code Modulation (ADPCM)-VBL

  • We proposed a novel stream-based method of visually lossless data compression that transfers image data in low latency and high quality applying ADPCM

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Summary

Introduction

The video data stream is one of main data streams utilized in the recent mobile and Internet of Things (IoT) applications. Surveillance camera systems [1] are widely used to detect irregular events in society [2,3] and home security [4] by applying machine learning methods [5,6] In such applications, a fast, seamless and high resolution video transmission improves the accuracy of the image processing for the video frames. Many techniques to overcome Shannon’s limit have been proposed and implemented such as the data compression technique that removes high and low frequencies in the image applying Fast Furrier Transform (FFT) and Discrete Cosine Transform (DCT) These lossy methods predict pixels in images from the reduced frequency information. The compressed data can become larger than the data size of the original image, it is mainly utilized as a lossy compression method

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