Inverse haiftoning is the problem of recovering a continuous-tone image from a given haiftoned image. In this paper, a new inverse haiftoning method which uses a set theoretic formulation is introduced. The new method exploits the prior information at hand, and uses space-domain projections, frequency-domain projections, and space-scale domain projections to obtain a feasible reconstruction of the continuous-tone image. The proposed method is also extended for the inverse halftoning of color error-diffused images.

No abstract

Abstract. Printing color images on color printers and displaying them on computer monitors requires a significant reduction of physically distinct colors, which causes degradation in image quality. An efficient method to improve the display quality of a quantized image is error diffusion, which works by distributing the previous quantization errors to neighboring pixels, exploiting the eye's averaging of colors in the neighborhood of the point of interest. This creates the illusion of more colors. A new error diffusion method is presented in which the adaptive recursive leastsquares (RLS) algorithm is used. This algorithm provides local optimization of the error diffusion filter along with smoothing of the filter coefficients in a neighborhood. To improve the performance, a diagonal scan is used in processing the image. © 2000 Society of Photo-Optical Instrumentation Engineers. [S0091-3286(00)