Demosaicing Using MFIT (Matrix Factorization Iterative Tunable) Based on Convolution Neural Network

  • Shabana TabassumEmail author
  • SanjayKumar C. Gowre
Conference paper
Part of the Lecture Notes on Data Engineering and Communications Technologies book series (LNDECT, volume 38)


Demosaicing is introduced for estimation of the other missing color for producing the absolute color image. Enormous research has been done in past to develop the Demosaicing algorithm, however all these methods have shortcomings, hence in this paper, we propose an algorithm called MF-IT (Matrix Factorization Iterative Tunable), this methodology is based on the CNN (Convolution Neural Network), the main aim of this research is to improvise the reconstruction quality of the given image. This is achieved by using the image-block adjustments based transform, which helps in utilizing the image block based transform. One of the main advantage of MFIT is shift invariance, which can be easily obtained without any support of striding image blocks. Henceforth, In order to evaluate the performance of our methodology it is compared against the various state-of-art method. The result analysis shows that proposed methodology simply outperforms the other method.


Demosaicing Image block Stride Non-stride 


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© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.Department of E&CEKBN College of EngineeringKalaburagiIndia
  2. 2.Department of E&CEBKITBhalkiIndia

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