| || ANAMICA: A Medical Data Visualisation and Characterisation
Author : Sundar, R.;Venkataramanan, N.;Srinivasan, N. ;Ramesh, N.;Athithan, G.
Source : Defence Science Journal ; Vol:43(3) ; 1993 ; pp 243-252
Subject : 57.089 Biomedical Sciences
Keywords : Computer tomography;Magnetic risonance imaging;Image processing;Histograms
Abstract : This paper reports the design and implementation of ANAMICA, a three-dimensional (3-D) medical data visualisation and characterisation system which provides a complete set of image processing options. Constructions of internal surfaces from total or partial volume of 3-D data and cut-out views are supported by means of 'volume rendering' as well as object space methods. Arbitrary planar and curved sections of 3-D data can be obtained and processed subsequently as standard 2-D images. Volumetrics and a preliminary characterisation of tissues based on histograms are also supported. A window based user-interface provides convenient access to all these options.
| || Pre-processing Algorithm for Rectification of Geometric Distortions in Satellite Images
Author : Panigrahi, Narayan;Mohan, B.K.;Athithan, G.
Source : Defence Science Journal ; Vol:61(2) ; 2011 ; pp 174-179
Subject : 681.3 Computer Science
Keywords : Input-to-output image transformation;polynomial affine transformation;ortho-rectification;pre-processing algorithm;image rectification;satellite images;image registration
Abstract : A number of algorithms have been reported to process and remove geometric distortions in satellite images. Ortho-correction, geometric error correction, radiometric error removal, etc are a few important examples. These algorithm require supplementary meta-information of the satellite images such as ground control points and correspondence, sensor orientation details, elevation profile of the terrain, etc to establish corresponding transformations. In this paper, a pre-processing algorithm has been proposed which removes systematic distortions of a satellite image and thereby removes the blank portion of the image. It is an input-to-output mapping of image pixels, where the transformation computes the coordinate of each output pixel corresponding to the input pixel of an image. The transformation is established by the exact amount of scaling, rotation and translation needed for each pixel in the input image so that the distortion induced during the recording stage is corrected.