An Effective Multi-focus Image Fusion Based on Law’s of Texture Enegery Measures in Integrated Wavelet Domain


  • Kiran S. Associate Professor and principal investigator, Department of CSE, YSR Engineering College of YVU, Proddatur, Kadapa, AP, India-516360


NSCT, DTCWT, LTEM, Texture, Image fusion


Feature extraction provides better description of given image. In computer vision, characterization of images is a challenging task. Due to intensity variations and non-uniformities. In such situations the texture description plays a vital role to extract essential information without any distortion, to attain such information texture energy measures are very useful. This paper concentrates on feature extraction methods by combining NSCT (Non-Subsampled Contourlet Transform) domain with the combination of DTCWT (Dual-Tree Complex Wavelet Transforms). Energy measures are applied in the form of masks to get more efficient features comparing with other approaches. A set of test images are considered to the energy measures which significantly improves correlation of texture for given test dataset. Different kinds of measures are considered like average gradient, edge intensity, gray mean value, standard deviation etc. to show the significance of proposed method with greater time complexity.


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DTCWT flow diagram




How to Cite

S., K. . (2023). An Effective Multi-focus Image Fusion Based on Law’s of Texture Enegery Measures in Integrated Wavelet Domain. International Journal of Intelligent Systems and Applications in Engineering, 11(6s), 67–75. Retrieved from



Research Article