Efficient, edge-aware, combined color quantization and dithering

Abstract—In this paper we present a novel algorithm to simultaneously accomplish color quantization and dithering of images. This is achieved by minimizing a perception-based cost function which considers pixel-wise differences between filtered versions of the quantized image and the input image. We use edge aware filters in defining the cost function to avoid mixing colors on opposite sides of an edge. The importance of each pixel is weighted according to its saliency. To rapidly minimize the cost function, we use a modified multi-scale iterative conditional mode (ICM) algorithm which updates one pixel a time while keeping other pixels unchanged. As ICM is a local method, careful initialization is required to prevent termination at a local minimum far from the global one. To address this problem, we initialize ICM with a palette generated by a modified median-cut method. Compared to previous approaches, our method can produce high quality results with fewer visual artifacts but also requires significantly less computational effort. Index Terms—Color quantization, dithering, optimization-based image processing. I

Adaptive methods for dithering color images

Cataloged from PDF version of article.Most color image printing and display devices do not have the capability of reproducing true color images. A common remedy is the use of dithering techniques that take advantage of the lower sensitivity of the eye to spatial resolution and exchange higher color resolution with lower spatial resolution. In this paper, an adaptive error diffusion method for color images is presented. The error diffusion filter coefficients are updated by a normalized least mean square-type (LMS-type) algorithm to prevent textural contours, color impulses, and color shifts, which are among the most common side effects of the standard dithering algorithms. Another novelty of the new method is its vector character: Previous applications of error diffusion have treated the individual color components of an image separately. Here, we develop a general vector approach and demonstrate through simulation studies that superior results are achieved. © 1997 IEEE

Improvements to the color quantization process

The presentation of color images on devices with limited color capabilities requires a reduction in the number of colors contained in the images. Color image quantization is the process of reducing the number of colors used in an image while maintaining its appearance as much as possible. This reduction is performed using a color image quantization algorithm. The quantization algorithm attempts to select k colors that best represent the contents of the image. The original image is then recolored using the representative colors. to improve the resulting image, a dithering process can be used in place of the recoloring.;This dissertation deals with several areas of the color image quantization process. The main objective, however, is new or improved algorithms for the production of images with a better visual quality than those produced by existing algorithms while maintaining approximately the same running time. First, a new algorithm is developed for the selection of the representative color set. The results produced by the new algorithm are better both visually and quantitatively when compared to existing algorithms. Second, a new nearest-neighbor search algorithm that is based on the Locally Sorted Search algorithm is developed to reduce the time required to map the input colors to a representative color. Finally, two modifications are made to the error-diffusion dithering technique that improve the execution time. These modifications include the use of a two-weight matrix for the distribution of the error values and the presentation of a method to parallelize the error-diffusion technique. Furthermore, the analytical results of several experiments are provided to show the effectiveness each of these additions and improvements

Pushing the Limits of 3D Color Printing: Error Diffusion with Translucent Materials

Accurate color reproduction is important in many applications of 3D printing, from design prototypes to 3D color copies or portraits. Although full color is available via other technologies, multi-jet printers have greater potential for graphical 3D printing, in terms of reproducing complex appearance properties. However, to date these printers cannot produce full color, and doing so poses substantial technical challenges, from the shear amount of data to the translucency of the available color materials. In this paper, we propose an error diffusion halftoning approach to achieve full color with multi-jet printers, which operates on multiple isosurfaces or layers within the object. We propose a novel traversal algorithm for voxel surfaces, which allows the transfer of existing error diffusion algorithms from 2D printing. The resulting prints faithfully reproduce colors, color gradients and fine-scale details.Comment: 15 pages, 14 figures; includes supplemental figure

Novel methods in image halftoning

Ankara : Department of Electrical and Electronics Engineering and Institute of Engineering and Science, Bilkent Univ., 1998.Thesis (Master's) -- Bilkent University, 1998.Includes bibliographical references leaves 97-101Halftoning refers to the problem of rendering continuous-tone (contone) images on display and printing devices which are capable of reproducing only a limited number of colors. A new adaptive halftoning method using the adaptive QR- RLS algorithm is developed for error diffusion which is one of the halftoning techniques. Also, a diagonal scanning strategy to exploit the human visual system properties in processing the image is proposed. Simulation results on color images demonstrate the superior quality of the new method compared to the existing methods. Another problem studied in this thesis is inverse halftoning which is the problem of recovering a contone image from a given halftoned image. A novel inverse halftoning method is developed for restoring a contone image from the halftoned image. A set theoretic formulation is used where sets are defined using the prior information about the problem. A new space domain projection is introduced assuming the halftoning is performed ,with error diffusion, and the error diffusion filter kernel is known. The space domain, frequency domain, and space-scale domain projections are used alternately to obtain a feasible solution for the inverse halftoning problem which does not have a unique solution. Simulation results for both grayscale and color images give good results, and demonstrate the effectiveness of the proposed inverse halftoning method.Bozkurt, GözdeM.S

Adaptive Quantisation in HEVC for Contouring Artefacts Removal in UHD Content

Contouring artefacts affect the visual experience of some particular types of compressed Ultra High Definition (UHD) sequences characterised by smoothly textured areas and gradual transitions in the value of the pixels. This paper proposes a technique to adjust the quantisation process at the encoder so that contouring artefacts are avoided. The devised method does not require any change at the decoder side and introduces a negligible coding rate increment (up to 3.4% for the same objective quality). This result compares favourably with the average 11.2% bit-rate penalty introduced by a method where the quantisation step is reduced in contour-prone areas