Showing papers on "Bilateral filter published in 1985"

Image compression technique

Abstract: An optical and electronic scan produces an image composed of binary value pixels. An automatic picture compression routine reduces the number of pixels in the image. A first stage four to one reduction in the number of pixels is achieved by treating each mutually exclusive four pixel unit as a separate set. A binary value is assigned to each four pixel set. That binary value is assigned to a single pixel in a first output image. The same process is repeated a second time to provide a final output image that has one-sixteenth the number of pixels as has the original input image. The value assigned to each four pixel unit set is a weighted function of the binary value of each of the sixteen pixels in a four pixel by four pixel subfield in which the unit set is centered. The greatest weight is give to the center pixels, that is, to the four pixels of the unit set. Lesser weight is given to the peripheral pixels. Among the peripheral pixels, lesser weight is given to the four corner pixels than is given to the eight side pixels between the corners. In the weighting process, the significance of the binary value of the sixteen pixels in the subfield is in part a function of the total pattern of the pixel values in the subfield.

Tree encoding of images using a nonlinear smoothing filter

Abstract: The DPCM system is often used for encoding images, but particularly in low-rate encoding methods, two types of noise of different nature (e.g., overload noise and granular noise) are introduced. In this paper a tree encoding scheme is applied to image signals and a design technique for an encoding filter is shown which is a combination of a least-mean-square filter derived from linear prediction theory and a nonlinear smoothing filter. The purpose of this nonlinear filter is to decrease the above-mentioned noise. Its construction is like that of an adaptive quantizer in which one of the preassigned output levels is selected, keeping in view the previously encoded symbols. The linear smoothing filter used in tree encoding of speech is a special case of this sytem. Moreover, the conditional mean output level for the present encoding symbol matches the output level of the Lloyd-Max quantizer for the Laplacian density function. The results obtained by applying this scheme to a head and shoulder image having clear boundaries are compared with the results without using a nonlinear smoothing filter and improvement of about 2 dB in SNR is obtained when the encoding rate is 1 bit/pixel.