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Content Provider | IEEE Xplore Digital Library |
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Author | Chih-Chang Lai Ching-Chih Tsai Jyun-Sian Li Ching-Fu Hsu |
Copyright Year | 2007 |
Description | Author affiliation: Nat. Chung-Hsing Univ., Taichung (Chih-Chang Lai; Ching-Chih Tsai) |
Abstract | For modern mobile phone displays, their driving integrated circuit (IC) solutions, often called total solutions, have included various functions, such as scanning, driving, power-level conversion, image storage memory, timing control, and standard interfacing; however, most of them lack of realtime image processing engine. In this paper, a novel real-time pixel-level image processing algorithm is presented to enlarge image color gamut and enhance image contrast without frame memory for mobile phone displays. This image processing algorithm simultaneously executes two parallel algorithms: rich color and contrast enhancement. The rich color algorithm obtains a wide color gamut image data showing more than 30% area enhancement in the CIE1931 color space without hue distortion. The contrast enhancement algorithm improves 20% contrast ratio improvement. Numerous simulation results are provided to illustrate the feasibility and efficacy of the proposed algorithms and image processing engine. Experimental results are conducted to show the performance and usefulness of the proposed composite algorithm for 2.2- inch mobile phone TFT LCDs. |
Starting Page | 2580 |
Ending Page | 2585 |
File Size | 2276892 |
Page Count | 6 |
File Format | |
ISBN | 1424407834 |
ISSN | 1553572X |
DOI | 10.1109/IECON.2007.4460173 |
Language | English |
Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Publisher Date | 2007-11-05 |
Publisher Place | Taiwan |
Access Restriction | Subscribed |
Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Subject Keyword | Mobile handsets Displays Image processing Image storage Engines Color Image converters Timing Pixel Parallel algorithms mobile phone color gamut contrast driver IC image processing |
Content Type | Text |
Resource Type | Article |
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