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

  • Authors:

  • Gustavo M. Callicó;Rafael Peset Llopis;Sebastian López;José Fco. López;Antonio Núñez;Ramanathan Sethuraman;Roberto Sarmiento

  • Affiliations:

  • The University of Las Palmas de Gran Canaria, Institute for Applied Microelectronics (IUMA), Tafira Baja, Spain;Philips Consumer Electronics, JB, The Netherlands;The University of Las Palmas de Gran Canaria, Institute for Applied Microelectronics (IUMA), Tafira Baja, Spain;The University of Las Palmas de Gran Canaria, Institute for Applied Microelectronics (IUMA), Tafira Baja, Spain;The University of Las Palmas de Gran Canaria, Institute for Applied Microelectronics (IUMA), Tafira Baja, Spain;Philips Research Laboratories, WDC, Eindhoven, The Netherlands;The University of Las Palmas de Gran Canaria, Institute for Applied Microelectronics (IUMA), Tafira Baja, Spain

  • Venue:
  • EURASIP Journal on Applied Signal Processing
  • Year:
  • 2006

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Abstract

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.