Sos S. Agaian

TL;DR: A general, efficient, manageable split algorithm to compute one-dimensional (1-D) unitary transforms, by using the special partitioning in the frequency domain, is introduced.

TL;DR: Preliminary results show that the presented algorithm out-performs other enhancement methods such as the traditional Fourier transform-based alpha-rooting and the multi-scale Retinex algorithms.

TL;DR: This paper proposes a logarithmic edge detection method that achieves a higher level of scene illumination and noise independence, and demonstrates the application of the algorithm in conjunction with Edge Detection based Image Enhancement (EDIE), showing that the use of this edge detection algorithm results in better image enhancement, as quantified by the Logarithic AME measure.

TL;DR: This study shows that the proposed term-by-term, fixed-threshold operator can perform as well as adaptively applied, scale-dependent soft and hard thresholding approaches.

TL;DR: New pixel- and region-based multiresolution image fusion algorithms are introduced in this paper using the Parameterized Logarithmic Image Processing (PLIP) model, a framework more suitable for processing images.