Low-cost super-resolution algorithms implementation over a HW/SW video compression platform

被引：0
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作者：
Callicó, Gustavo M. [1 ]
Llopis, Rafael Peset [2 ]
López, Sebastian [1 ]
López, José Fco. [1 ]
Núñez, Antonio [1 ]
Sethuraman, Ramanathan [3 ]
Sarmiento, Roberto [1 ]
机构：
[1] University of Las Palmas de Gran Canaria, Institute for Applied Microelectronics (IUMA), Tafira Baja, 35017, Spain
[2] Philips Consumer Electronics, SFJ-6, P.O. Box 80002, 5600 JB, Netherlands
[3] Philips Research Laboratories, WDC 3.33, Professor Holstlaan 4, AA 5656 Eindhoven, Netherlands
来源：
Eurasip Journal on Applied Signal Processing | 2006年 / 2006卷
关键词：
Two approaches are presented in this paper to improve the quality of digital images over the sensor resolution using super-resolution techniques: iterative super-resolution (ISR) and noniterative super-resolution (NISR) algorithms. The results show important improvements in the image quality; assuming that sufficient sample data and a reasonable amount of aliasing are available at the input images. These super-resolution algorithms have been implemented over a codesign video compression platform developed by Philips Research; performing minimal changes on the overall hardware architecture. In this way; a novel and feasible low-cost implementation has been obtained by using the resources encountered in a generic hybrid video encoder. Although a specific video codec platform has been used; the methodology presented in this paper is easily extendable to any other video encoder architectures. Finally a comparison in terms of memory; computational load; and image quality for both algorithms; as well as some general statements about the final impact of the sampling process on the quality of the super-resolved (SR) image; are also presented. Copyright © 2006 Hindawi Publishing Corporation. All right reserved;
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