Morphological Component Analysis

In the morphological diversity based framework, any signal is modeled as the linear combination of several morphological components.

Morphological Component Analysis has been devised to solve the recover the morphological components from their combination. Going back to the classical texture-contour separation. The MCA endeavours to recover the original texture and cartoon parts based on their morphological diversities.































Applications :


  1. PuceMCA for audio signals

  2. PuceSimulation with the curvelet transform and a trous wavelet transform

  3. PuceGalaxy image decomposition with wavelet, curvelet and ridgelet transforms

  4. PuceGravitational arc (Hubble Space Telescope) image decomposition

  5. PuceVarious image decompositions



MCA

 

Softwares :


  1. ❖MCALab

  2. ❖WaveLab

  3. ❖CurveLab

  4. ❖WaveAtom

References :


  1. ❖J. Bobin, J.-L. Starck, J. Fadili, Y. Moudden, and D.L. Donoho, "Morphological Component Analysis : An Adaptive Thresholding Strategy", IEEE Transactions on Image Processing, Vol.16, N°11, p. 2675 - 2681, November 2007.

  2. ❖M. Elad, J.-L Starck, D. Donoho and P. Querre, "Simultaneous Cartoon and Texture Image Inpainting using Morphological Component Analysis (MCA)", Journal on Applied and Computational Harmonic Analysis ACHA , Vol. 19, pp. 340-358, November 2005.

  3. ❖J.-L. Starck, M. Elad, and D.L. Donoho, "Image Decomposition Via the Combination of Sparse Representation and a Variational Approach", IEEE Transaction on Image Processing , Vol. 14, N°10, 2005.

  4. ❖J.-L. Starck, M. Elad, and D.L. Donoho, "Redundant Multiscale Transforms and their Application for Morphological Component Analysis", Advances in Imaging and Electron Physics , 132, 2004.