Locally adaptive reconstruction of lost low-frequency coefficients in wavelet coded images

Joost Rombaut; Aleksandra Pižurica; Wilfried Philips

doi:10.1117/12.698430

29 January 2007 Locally adaptive reconstruction of lost low-frequency coefficients in wavelet coded images

Joost Rombaut, Aleksandra Pižurica, Wilfried Philips

Proceedings Volume 6508, Visual Communications and Image Processing 2007; 65081R (2007) https://doi.org/10.1117/12.698430
Event: Electronic Imaging 2007, 2007, San Jose, CA, United States

Abstract

In packet switched networks such as the Internet, packets may get lost during transmission due to, e.g., network congestion. This leads to a quality degradation of the original signal. As video communication is a bandwidth consuming application, the original data are first compressed. This compression step increases the impact of information loss even more. In wavelet based image and video coding, the low frequency data is the most important. Loss of low frequency coefficients results in annoying black holes in the received images and video. This effect can be countered by post processing error concealment: a lost coefficient is estimated from its neighboring coefficients. In this paper we present a locally adaptive interpolation method for the lost low frequency coefficients. For each lost low frequency coefficient, we estimate the optimal interpolation direction (horizontal or vertical) using novel error measures. In this way, we preserve the edges in the reconstructed image much better. Compared to older techniques of similar complexity, our scheme reconstructs images with the same or better quality. This is reflected in the visual as well as in the numerical results: there is an increase of up to 4.4 dB compared to bilinear concealment. The proposed scheme is fast and simple, which makes it suitable for real-time applications.

Citation Download Citation

Joost Rombaut, Aleksandra Pižurica, and Wilfried Philips "Locally adaptive reconstruction of lost low-frequency coefficients in wavelet coded images", Proc. SPIE 6508, Visual Communications and Image Processing 2007, 65081R (29 January 2007); https://doi.org/10.1117/12.698430

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KEYWORDS

Image compression

Wavelets

Error analysis

Receivers

Video

Visualization

Signal attenuation

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