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

Digital Color Imaging

This paper surveys current technology and research in the area of digital color imaging. In order to establish the background and lay down terminology, fundamental concepts of color perception and measurement are first presented us-ing vector-space notation and terminology. Present-day color recording and reproduction systems are reviewed along with the common mathematical models used for representing these devices. Algorithms for processing color images for display and communication are surveyed, and a forecast of research trends is attempted. An extensive bibliography is provided

A POCS-based restoration algorithm for restoring halftoned color-quantized images

Centre for Multimedia Signal Processing, Department of Electronic and Information Engineering2006-2007 > Academic research: refereed > Publication in refereed journalVersion of RecordPublishe

Media processor implementations of image rendering algorithms

Demands for fast execution of image processing are a driving force for today\u27s computing market. Many image processing applications require intense numeric calculations to be done on large sets of data with minimal overhead time. To meet this challenge, several approaches have been used. Custom-designed hardware devices are very fast implementations used in many systems today. However, these devices are very expensive and inflexible. General purpose computers with enhanced multimedia instructions offer much greater flexibility but process data at a much slower rate than the custom-hardware devices. Digital signal processors (DSP\u27s) and media processors, such as the MAP-CA created by Equator Technologies, Inc., may be an efficient alternative that provides a low-cost combination of speed and flexibility. Today, DSP\u27s and media processors are commonly used in image and video encoding and decoding, including JPEG and MPEG processing techniques. Little work has been done to determine how well these processors can perform other image process ing techniques, specifically image rendering for printing. This project explores various image rendering algorithms and the performance achieved by running them on a me dia processor to determine if this type of processor is a viable competitor in the image rendering domain. Performance measurements obtained when implementing rendering algorithms on the MAP-CA show that a 4.1 speedup can be achieved with neighborhood-type processes, while point-type processes achieve an average speedup of 21.7 as compared to general purpose processor implementations

Rethinking PRL: A Multiscale Progressively Residual Learning Network for Inverse Halftoning

Image inverse halftoning is a classic image restoration task, aiming to recover continuous-tone images from halftone images with only bilevel pixels. Because the halftone images lose much of the original image content, inverse halftoning is a classic ill-problem. Although existing inverse halftoning algorithms achieve good performance, their results lose image details and features. Therefore, it is still a challenge to recover high-quality continuous-tone images. In this paper, we propose an end-to-end multiscale progressively residual learning network (MSPRL), which has a UNet architecture and takes multiscale input images. To make full use of different input image information, we design a shallow feature extraction module to capture similar features between images of different scales. We systematically study the performance of different methods and compare them with our proposed method. In addition, we employ different training strategies to optimize the model, which is important for optimizing the training process and improving performance. Extensive experiments demonstrate that our MSPRL model obtains considerable performance gains in detail restoration

Incorporating Edge Information in Digital Halftoning

Digital halftoning is the process of generating a binary image preserving gray shade information so as to make the binary image appears visually similar to gray image. It was used in printing machines and display devices to produce binary images having gray shades. Ordered dithering and error diffusion methods are two most popular methods to generate halftone image. Generally, in a halftone image, the edges become blurred or loses its sharpness. Edges carry significant information of the foreground objects in an image and increase visual clarity by distinguishing the objects from background. A method is proposed to generate edge sharpened halftone images using a strong unsharp masks. Such edge sharpened halftone images are visually more pleasing and informative as compared with the normal halftone images. The proposed method is found to be better than Xin-Li’s edge-adaptive method of generating halftone images.Keywords: Digital halftoning, edge enhancement, unsharp masking, error diffusion, Sierra’s Filter*Cite as: Yumnam Kirani Singh, “Incorporating Edge Information in Digital Halftoning†ADBU J.Engg Tech., 1(2014) 0011403(6pp

Parallel Algorithms for Look-Up Table (LUT) Inverse Halftoning

The Look-Up Table (LUT) method for inverse halftoning is fast and computation-free technique employed to obtain good quality images. In this work we propose six algorithms to parallelize the LUT method so that more pixels can be concurrently inverse halftone using minimum additional hardware. The proposed algorithms partition the single LUT of serial LUT method into N smaller Look-Up Tables (s − LUTs) such that the total number of contents in all s−LUTs remain equal to the number of contents in the single LUT of serial LUT method. The proposed parallel algorithms have image quality equal to the serial LUT method when gain in clock cycles over the serial method is less and have lesser image quality comparetively to serial LUT method when gain in clock cycles over the serial method is very high. The parallel algorithms can be implemented on FPGA (Field Programmable Gate Arrays) devices with external CAM (Content Addressable Memories) and ROM (Read Only Memories)

Parallel Algorithms for Look-Up Table (LUT) Inverse Halftoning

The Look-Up Table (LUT) method for inverse halftoning is fast and computation-free technique employed to obtain good quality images. In this work we propose six algorithms to parallelize the LUT method so that more pixels can be concurrently inverse halftone using minimum additional hardware. The proposed algorithms partition the single LUT of serial LUT method into N smaller Look-Up Tables (s − LUTs) such that the total number of contents in all s−LUTs remain equal to the number of contents in the single LUT of serial LUT method. The proposed parallel algorithms have image quality equal to the serial LUT method when gain in clock cycles over the serial method is less and have lesser image quality comparetively to serial LUT method when gain in clock cycles over the serial method is very high. The parallel algorithms can be implemented on FPGA (Field Programmable Gate Arrays) devices with external CAM (Content Addressable Memories) and ROM (Read Only Memories)