Low power techniques for video compression

This paper gives an overview of low-power techniques proposed in the literature for mobile multimedia and Internet applications. Exploitable aspects are discussed in the behavior of different video compression tools. These power-efficient solutions are then classified by synthesis domain and level of abstraction. As this paper is meant to be a starting point for further research in the area, a lowpower hardware & software co-design methodology is outlined in the end as a possible scenario for video-codec-on-a-chip implementations on future mobile multimedia platforms

PEA265: Perceptual Assessment of Video Compression Artifacts

The most widely used video encoders share a common hybrid coding framework that includes block-based motion estimation/compensation and block-based transform coding. Despite their high coding efficiency, the encoded videos often exhibit visually annoying artifacts, denoted as Perceivable Encoding Artifacts (PEAs), which significantly degrade the visual Qualityof- Experience (QoE) of end users. To monitor and improve visual QoE, it is crucial to develop subjective and objective measures that can identify and quantify various types of PEAs. In this work, we make the first attempt to build a large-scale subjectlabelled database composed of H.265/HEVC compressed videos containing various PEAs. The database, namely the PEA265 database, includes 4 types of spatial PEAs (i.e. blurring, blocking, ringing and color bleeding) and 2 types of temporal PEAs (i.e. flickering and floating). Each containing at least 60,000 image or video patches with positive and negative labels. To objectively identify these PEAs, we train Convolutional Neural Networks (CNNs) using the PEA265 database. It appears that state-of-theart ResNeXt is capable of identifying each type of PEAs with high accuracy. Furthermore, we define PEA pattern and PEA intensity measures to quantify PEA levels of compressed video sequence. We believe that the PEA265 database and our findings will benefit the future development of video quality assessment methods and perceptually motivated video encoders.Comment: 10 pages,15 figures,4 table

Lossless Video Compression

Tato bakalářská práce se zabývá bezeztrátovou kompresí videa s použitím 3D predikce. Nejdříve je uvedena nezbytná teorie kolem úpravy obrazových dat a bezeztrátové komprese. Tato část slouží k vymezení důležitých pojmů, které jsou potřeba k samostatné tvůrčí činnosti. Následuje návrh několika variant struktury kodeku, výběr metod k implementaci a popis očekávaných vlastností. Zde lze získat první představu o způsobu fungování kodeku. Poté jsou popsány některé implementační detaily, které pomohou vytvořit přehled o vnitřní architektuře. Vlastnosti výsledného kodeku jsou nakonec otestovány a porovnány s jinými kodeky. Ukázalo se, že vlastní kodek používající 3D predikci dokáže kompresním poměrem překonat všechny ostatní kodeky v testu.This thesis is about the lossless video compression using 3D prediction. At first is introduced the necessary theory about image data modification. This part serves to define important terms, which are needed to start the creative work itself. Then several variants of codec's structure proposals follow, as well as the choice of methods and description of expected characteristics. Here we can get the first idea how the codec works. Then there is a description of some implementation's details, which could give a detailed insight into the codec's inner architecture. In the last part of the work, the implemented codec is tested and its characteristics are compared to another lossless codecs. The result is that the own codec, using the 3D prediction, can defeat all other tested codecs with its compression ratio.

Study and simulation of spatial video compression for remotely piloted vehicles

Techniques of video compression applicable to remotely piloted vehicles (RPVs) are investigated. One approach is to reduce the frame rate, the other is to reduce the number of bits per sample needed to represent static picture detail by means of digital video compression. Hadamard transforms of 8 x 8 subpictures, with adaptive and nonadaptive quantization of transform coefficients, were investigated for the latter technique. Tapes of typical RPV video, processed by Aeronautronic Ford to simulate four frame rates, were again processed by the Ames real-time video system to obtain a variety of compressions of each of the four frame rates