Mixed digital image halftoning method based on significance visual attention model

Abstract

The invention relates to a mixed digital image halftoning method based on a significance visual attention model, and belongs to the technical field of image processing. The method is characterized by adopting a bottom-up visual selective attention model, and carrying out calculation to obtain image intensity, color and direction feature patterns from an input image through Gaussian pyramids and a "center-surround" operator; carrying out normalization on the feature patterns to enable the feature patterns to be superposed into a total significance pattern, and extracting regions of interest (ROIs) of the image; carrying out image halftoning on the images in the ROIs through a model-based weighted least square halftone iteration method; carrying out halftone image conversion in non regions-of-interest (NROI) through a tone-based error diffusion method, and carrying out halftone parallel computing in the two regions of the image; and objectively evaluating digital image halftoning performance through a quality evaluation method based on the selective attention model, and analyzing algorithm complexity to obtain an optimum halftone image.

Description

Technical field [0001] The invention relates to a hybrid digital image halftone method of a saliency visual attention model, which belongs to the technical field of image processing and is suitable for digital image pre-press processing technology in the field of printing and publishing. Background technique [0002] Digital halftone is an important support technology for computer input / output, which solves the contradiction that devices with only binary reproduction capabilities cannot directly output multi-gray-level images. For continuous tone images, digital image halftone technology must be used to convert them into black and white binary images suitable for output before output. Therefore, the digital halftone algorithm of continuous tone images plays a particularly critical role in image output. [0003] The reason why halftone can simulate a continuous tone image depends on the characteristics of the low-pass or band-pass filter of the human visual system, and the quality o...

AI Technical Summary

Problems solved by technology

The ordered dithering algorithm has low complexity. It only needs to compare the gray value of each pixel in the image with the spatial variation threshold one by one, and determine the binary value of the halftone image according to the comparison result. This method is fast and simple, but the obtained image quality is the lowest. of

The error diffusion algorithm is to diffuse the quantization error of the current pixel to adjacent pixels in a certain proportion, so that the local quantization error is compensated on the adjacent pixels, resulting in a halftone image with smooth texture in the clear reproduction area of ​​the image. However, This method also produces a "worm" phenomenon

The optimization method realizes digital image halftone by calculating the optimal configuration of binary pixels that minimizes the perceptual error measure, but it requires a lot of calculations and is not feasible for some real-time applications

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