Adaptive Acceleration of MAP with Entropy Prior and Flux Conservation for Image Deblurring

  • Manoj Kumar Singh
  • Yong-Hoon Kim
  • U. S. Tiwary
  • Rajkishore Prasad
  • Tanveer Siddique
Conference paper


In this paper we present and adaptive method for accelerating conventional Maximum a Posteriori (MAP) with Entropy prior (MAPE) method for restoration of an original image from its blurred and noisy version. MAPE method is nonlinear and its convergence is very slow. We present a new method to accelerate the MAPE algorithm by using an exponent on the correction ratio. In this method the exponent is computed adaptively in each iteration, using first-order derivatives of deblurred images in previous two iterations. The exponent obtained so in the proposed accelerated MAPE algorithm emphasizes speed at the beginning stages and stability at later stages. In the accelerated MAPE algorithm the non-negativity is automatically ensured and also conservation of flux without additional computation. The proposed accelerated MAPE algorithm gives better results in terms of RMSE, SNR, moreover, it takes 46% lesser iterations than conventional MAPE.


Point Spread Function MAPE Algorithm Markov Random Field Correction Ratio Acceleration Method 
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Copyright information

© Indian Institute of Information Technology, India 2009

Authors and Affiliations

  • Manoj Kumar Singh
    • 1
  • Yong-Hoon Kim
    • 2
  • U. S. Tiwary
    • 3
  • Rajkishore Prasad
    • 4
  • Tanveer Siddique
    • 3
  1. 1.Dept. of Computer Science and EngineeringGalgotiya College of Engineering and TechnologyIndia
  2. 2.Sensor System Laboratory, Department of MechatronicsGwangju Institute of Science and Technology (GIST)Republic of Korea
  3. 3.Indian Institute of Information Technology Allahabad(IIITA)India
  4. 4.University of Electro-CommunicationTokyoJapan

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