Accelerating digital halftoning using the local exhaustive search on the GPU. (12th February 2016)

• Record Type: Journal Article
• Authors: Kouge, Hiroaki; Honda, Takumi; Fujita, Toru; Ito, Yasuaki; Nakano, Koji; Bordim, Jacir L.
• Other Names: Grosu Daniel guestEditor.; Jin Hai guestEditor.; Maheshwari Ketan guestEditor.; Katz Daniel guestEditor.; Olabarriaga Silvia D. guestEditor.; Wozniak Justin guestEditor.; Thain Douglas guestEditor.
• Is Part Of: Concurrency and computation. Volume 29:Number 2(2017)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2016-02-12
• Subjects: image processing -- digital halftoning -- GPGPU -- local exhaustive search -- cluster‐dot halftoning; Parallel processing (Electronic computers) -- Periodicals; Parallel computers -- Periodicals; 004.35
• DOI: 10.1002/cpe.3781
• Languages: English
• ISSNs: 1532-0626

Abstract

Summary: Digital halftoning is an important process to convert a grayscale image into a binary image with black and white pixels. Local exhaustive search‐based halftoning is one of the halftoning methods that can generate high‐quality binary images. However, considering the computing time, it is not realistic for most applications. As a first contribution, this paper proposes a graphics processing unit (GPU) implementation for digital halftoning employing local exhaustive search to produce high‐quality binary images. Programming issues of the GPU architecture have been carefully assessed for implementing the proposed method. Experimental results show that the proposed GPU implementation on NVIDIA (Santa Clara, CA, USA) GeForce GTX TITAN X attains a speed‐up factor of up to 48 over a CPU implementation. Our second contribution is a GPU implementation for cluster‐dot halftoning tailored for local exhaustive search. This implementation attains a speed‐up factor of 92 over a sequential CPU implementation. Copyright © 2016 John Wiley & Sons, Ltd.