6,295 research outputs found
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
Quality Adaptive Least Squares Trained Filters for Video Compression Artifacts Removal Using a No-reference Block Visibility Metric
Compression artifacts removal is a challenging problem because videos can be compressed at different qualities. In this paper, a least squares approach that is self-adaptive to the visual quality of the input sequence is proposed. For compression artifacts, the visual quality of an image is measured by a no-reference block visibility metric. According to the blockiness visibility of an input image, an appropriate set of filter coefficients that are trained beforehand is selected for optimally removing coding artifacts and reconstructing object details. The performance of the proposed algorithm is evaluated on a variety of sequences compressed at different qualities in comparison to several other deblocking techniques. The proposed method outperforms the others significantly both objectively and subjectively
Improvement of Text Dependent Speaker Identification System Using Neuro-Genetic Hybrid Algorithm in Office Environmental Conditions
In this paper, an improved strategy for automated text dependent speaker identification system has been proposed in noisy environment. The identification process incorporates the Neuro-Genetic hybrid algorithm with cepstral based features. To remove the background noise from the source utterance, wiener filter has been used. Different speech pre-processing techniques such as start-end point detection algorithm, pre-emphasis filtering, frame blocking and windowing have been used to process the speech utterances. RCC, MFCC, ?MFCC, ??MFCC, LPC and LPCC have been used to extract the features. After feature extraction of the speech, Neuro-Genetic hybrid algorithm has been used in the learning and identification purposes. Features are extracted by using different techniques to optimize the performance of the identification. According to the VALID speech database, the highest speaker identification rate of 100.000% for studio environment and 82.33% for office environmental conditions have been achieved in the close set text dependent speaker identification system
Scaling in the Positive Plaquette Model and Universality in SU(2) Lattice Gauge Theory
We investigate universality, scaling, the beta-function and the topological
charge in the positive plaquette model for SU(2) lattice gauge theory.
Comparing physical quantities, like the critical temperature, the string
tension, glueball masses, and their ratios, we explore the effect of a complete
suppression of a certain lattice artifact, namely the negative plaquettes, for
SU(2) lattice gauge theory. Our result is that this modification does not
change the continuum limit, i.e., the universality class. The positive
plaquette model and the standard Wilson formulation describe the same physical
situation. The approach to the continuum limit given by the beta-function in
terms of the bare lattice coupling, however, is rather different: the
beta-function of the positive plaquette model does not show a dip like the
model with standard Wilson action.Comment: 35 pages, preprint numbers FSU-SCRI-94-71 and HU Berlin-IEP-94/1
Perceptually-Driven Video Coding with the Daala Video Codec
The Daala project is a royalty-free video codec that attempts to compete with
the best patent-encumbered codecs. Part of our strategy is to replace core
tools of traditional video codecs with alternative approaches, many of them
designed to take perceptual aspects into account, rather than optimizing for
simple metrics like PSNR. This paper documents some of our experiences with
these tools, which ones worked and which did not. We evaluate which tools are
easy to integrate into a more traditional codec design, and show results in the
context of the codec being developed by the Alliance for Open Media.Comment: 19 pages, Proceedings of SPIE Workshop on Applications of Digital
Image Processing (ADIP), 201
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