Showing papers on "Image scaling published in 1982"
01 Dec 1982-Graphical Models \/graphical Models and Image Processing \/computer Vision, Graphics, and Image Processing
TL;DR: A parametric implementation of cubic convolution image reconstruction is presented which is generally superior to the standard algorithm and which can be optimized to the frequency content of the image.
Abstract: Cubic convolution, which has been discussed by Rifman and McKinnon (1974), was originally developed for the reconstruction of Landsat digital images. In the present investigation, the reconstruction properties of the one-parameter family of cubic convolution interpolation functions are considered and thee image degradation associated with reasonable choices of this parameter is analyzed. With the aid of an analysis in the frequency domain it is demonstrated that in an image-independent sense there is an optimal value for this parameter. The optimal value is not the standard value commonly referenced in the literature. It is also demonstrated that in an image-dependent sense, cubic convolution can be adapted to any class of images characterized by a common energy spectrum.
349 citations
TL;DR: An approach to performing resampling in an SIMD environment is given, and computational speedup over conventional uniprocessor approaches is shown to be approximately a factor of N where N is the number of processors used.
Abstract: Due to advances in VLSI technology, large scale arrays of microprocessors forming parallel processing systems have become feasible. The use of such a microprocessor array operating in the SIMD (single instruction stream-multiple data stream) mode to perform image resampling is explored. A general theory of resampling in terms of offsets is developed. From this, an approach to performing resampling in an SIMD environment is given. Detailed analysis of the SIMD algorithm is presented, and computational speedup over conventional uniprocessor approaches is shown to be approximately a factor of N where N is the number of processors used.
23 citations
TL;DR: Interpolation is found to have no effect on perceptual tasks, but 'random interpolation' produced a more pleasing image than simple linear interpolation.
Abstract: The effect of picture element (pixel) size on image quality is investigated. Asked simply to state their preference for clinical images displayed with different pixel sizes, observers preferred those with the smallest pixel. Specific perceptual tasks, however, such as abnormality detection, are found to be insensitive to changes in pixel size up to a limit. Interpolation is found to have no effect on perceptual tasks, but 'random interpolation' produced a more pleasing image than simple linear interpolation.
8 citations
01 May 1982
TL;DR: In order to automatize this procedure, two algorithms are presented with their advantages and drawbacks:Cubic convolution interpolation and Spline interpolation.
Abstract: A quick identification of the received image is a desirable feature in low bandwith transmission systems. A gross quality approximation of the image is obtained at early stages when it is hierarchically encoded. This allows faster recognition than raster scanning methods, without transmission overhead. Spline interpolation facilitates this process, greatly improving the efficiency of hierarchical approaches. The same subjective impression is obtained with half of the information. Cubic convolution interpolation has all the advantages of the former, and can be more easily calculated. Recognition with less amount of received bits can be achieved with a non uniform development of the hierarchy. In order to automatize this procedure, two algorithms are presented with their advantages and drawbacks. In all the considered cases, transmission can be ended when the receiver decides. So, compression can be achieved at the cost of an approximation errors.
6 citations