A Hybrid Digital Image Halftoning Method Based on a Salient Visual Attention Model

Abstract

The invention relates to a hybrid digital image halftone method of saliency visual attention model, and belongs to the technical field of image processing. The invention applies a bottom-up visual selective attention model to calculate feature maps of image intensity, color and direction from the input image through Gaussian pyramid and "center-periphery" operator. Each feature map is normalized and superimposed into a total saliency map, and the region of interest ROIs of the image are extracted. A model-based weighted least squares halftoning iteration method is used to halftonize the image in ROIs. The hue-based error diffusion method is used to convert halftone images in non-interest areas, and halftones are calculated in parallel in two areas of the image. The quality evaluation method based on the selective attention model is applied to objectively evaluate the performance of digital image halftones, and the complexity of the algorithm is analyzed to obtain the optimal halftone image.

Description

technical field [0001] The invention relates to a hybrid digital image halftone method of a salient visual attention model, which belongs to the technical field of image processing and is suitable for digital image prepress processing technology in the field of printing and publishing. Background technique [0002] Digital halftone is an important supporting technology for computer input / output, which solves the contradiction that devices with only binary reproduction capabilities cannot directly output multi-grayscale images. For the continuous tone image, it must be converted into a black and white binary image suitable for output through digital image halftone technology before output, so the digital halftone algorithm of the continuous tone image plays a particularly critical role in the image output effect. [0003] The reason why halftones can simulate continuous tone images depends on the characteristics of the low-pass or band-pass filters of the human visual system,...

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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