Two adaptive methods based on edge analysis for improved concealing damaged coded images in critical error situations

Alejandro Alvaro Ramírez-Acosta, Mireya S. García-Vázquez

Producción científica: Capítulo del libro/informe/acta de congresoContribución a la conferenciarevisión exhaustiva

Resumen

The original coded image signal can be affected when it is transmitted over error-prone networks. Error concealment techniques for compressed image or video attempt to exploit correctly received information to recover corrupted regions that are lost. If these regions have edges, most of these conventional approaches cause noticeable visual degradations, because they not consider the edge characteristics of images. The spatial error concealment methods cannot work well; especially over high burst error condition since a great of neighboring information have been corrupted or lost (called 'critical error situations'). This paper proposes two adaptive and effective methods to select the required support area, based on edge analysis using local geometric information, suited base functions and optimal expansion coefficients, in order to conceal the damaged macroblocks in critical error situations. Experimental results show that the proposed two approaches outperform existing methods by up to 7.9 dB on average.

Idioma originalInglés
Título de la publicación alojadaAdvances in Artificial Intelligence - 11th Mexican International Conference on Artificial Intelligence, MICAI 2012, Revised Selected Papers
Páginas158-170
Número de páginas13
EdiciónPART 1
DOI
EstadoPublicada - 2013
Evento11th Mexican International Conference on Artificial Intelligence, MICAI 2012 - San Luis Potosi, México
Duración: 27 oct. 20124 nov. 2012

Serie de la publicación

NombreLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NúmeroPART 1
Volumen7629 LNAI
ISSN (versión impresa)0302-9743
ISSN (versión digital)1611-3349

Conferencia

Conferencia11th Mexican International Conference on Artificial Intelligence, MICAI 2012
País/TerritorioMéxico
CiudadSan Luis Potosi
Período27/10/124/11/12

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