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Proceedings ArticleDOI

Rate scalable video coding using a foveation-based human visual system model

TLDR
This work proposes a foveation scalable video coding (FSVC) algorithm, which supplies good quality-compression performance as well as effective rate scalability to support simple and precise bit rate control.
Abstract
Recently, there have been two interesting trends in image and video coding research. One is to use human visual system (HVS) models to improve the current state-of-the-art coding algorithms by better exploiting the properties of the intended receiver. The other is to design rate-scalable video codecs, which allow the extraction of coded visual information at continuously varying bit rates from a single compressed bitstream. We follow these two trends and propose a foveation scalable video coding (FSVC) algorithm, which supplies good quality-compression performance as well as effective rate scalability to support simple and precise bit rate control. A foveation-based HVS model plays a key role in the algorithm. The algorithm is amenable to the inclusion of various HVS models and adaptable to different video communication applications.

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Citations
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Proceedings Article

Image Processing

TL;DR: The main focus in MUCKE is on cleaning large scale Web image corpora and on proposing image representations which are closer to the human interpretation of images.
Journal ArticleDOI

Human visual system based adaptive digital image watermarking

TL;DR: A new adaptive digital image watermarking method that is built according to the image features such as the brightness, edges, and region activities and extended to the DCT domain by searching the extreme value of the quadratic function subject to the bounds on the variables.
Proceedings ArticleDOI

Predictive perceptual compression for real time video communication

TL;DR: This paper has developed an eye gaze-aware MPEG-2 transcoder that can perceptually re-encode a live video stream in real time and compensates the interim eye movements between the sampling and actual coding.
Journal ArticleDOI

A practical foveation-based rate-shaping mechanism for MPEG videos

TL;DR: An efficient and practical DCT-domain foveation model, which is deduced from existing experimental results, and an efficient rate-shaping mechanism for MPEG bitstreams, which are practical for real-world usage.
Patent

Method and apparatus for data compression using content-based features

TL;DR: In this article, the authors present methods and apparatuses for compressing a video signal, including storing a function derived from a set of human ratings in a memory, identifying within at least a portion of the video signal at least one content-based feature, inputting the identified contentbased feature into the stored function, determining a compression ratio based on the function using a processor and generating a compressed video signal with the determined compression ratio.
References
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Journal ArticleDOI

A new, fast, and efficient image codec based on set partitioning in hierarchical trees

TL;DR: The image coding results, calculated from actual file sizes and images reconstructed by the decoding algorithm, are either comparable to or surpass previous results obtained through much more sophisticated and computationally complex methods.
Journal ArticleDOI

Embedded image coding using zerotrees of wavelet coefficients

TL;DR: The embedded zerotree wavelet algorithm (EZW) is a simple, yet remarkably effective, image compression algorithm, having the property that the bits in the bit stream are generated in order of importance, yielding a fully embedded code.
Book

Eye Movements and Vision

Proceedings Article

Image Processing

TL;DR: The main focus in MUCKE is on cleaning large scale Web image corpora and on proposing image representations which are closer to the human interpretation of images.
Journal ArticleDOI

Visibility of wavelet quantization noise

TL;DR: A mathematical model is constructed for DWT noise detection thresholds that is a function of level, orientation, and display visual resolution that allows calculation of a "perceptually lossless" quantization matrix for which all errors are in theory below the visual threshold.
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