Showing papers on "Image scaling published in 1983"

Comparison of Interpolating Methods for Image Resampling

Abstract: When resampling an image to a new set of coordinates (for example, when rotating an image), there is often a noticeable loss in image quality. To preserve image quality, the interpolating function used for the resampling should be an ideal low-pass filter. To determine which limited extent convolving functions would provide the best interpolation, five functions were compared: A) nearest neighbor, B) linear, C) cubic B-spline, D) high-resolution cubic spline with edge enhancement (a = -1), and E) high-resolution cubic spline (a = -0.5). The functions which extend over four picture elements (C, D, E) were shown to have a better frequency response than those which extend over one (A) or two (B) pixels. The nearest neighbor function shifted the image up to one-half a pixel. Linear and cubic B-spline interpolation tended to smooth the image. The best response was obtained with the high-resolution cubic spline functions. The location of the resampled points with respect to the initial coordinate system has a dramatic effect on the response of the sampled interpolating function?the data are exactly reproduced when the points are aligned, and the response has the most smoothing when the resampled points are equidistant from the original coordinate points. Thus, at the expense of some increase in computing time, image quality can be improved by resampled using the high-resolution cubic spline function as compared to the nearest neighbor, linear, or cubic B-spline functions.

Shape-Preserving Planar Interpolation: An Algorithm

Abstract: If a computer and a draftsman are asked to draw a curve through identical planar data, the draftsman's curve frequently looks better. Must it be this way?

Image Sequence Coding Using Scene Analysis and Spatio-Temporal Interpolation

Abstract: In video-conferencing or monitoring applications it might be desirable to use data channels with very low bandwidth. In order to achieve bit rates of 64kBit/s and less in seems inevitable to subsample the input scene in time. Therefore the reciever will have to perform a spatio-temporal interpolation of the transmitted key-frames in order to reconstruct the missing in-between images. To do this properly, further information about the moving parts of the scene, derived by scene analysis, has to be transmitted. The segmentation procedure as well as the interpolation procedure are presented.

Methods for image interpolation through FIR filter design techniques

Abstract: Interpolation methods in image processing are necessary in various applications. In this work the problem of image interpolation is approached from the viewpoint of digital signal processing. This paper presents a two-dimensional extension of earlier work in one dimension. A class of image interpolators is thus obtained and may be compared with the more common ones, such as nearest-neighbor, bilinear and cubic convolution.

Image Sampling And Interpolation

Abstract: Various methods for image sampling and inter olation are considered. The use of Nyquist sampling is discussed; interpolation of sampled data by the use of pp-functions and B-splines is introduced; and the various methods are compared for the case of image samling. An elementary introduction to B-splines and their applications is given in a manner that lacks rigor but which should appeal to engineers.© (1983) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.