在現今智慧型裝置如手機、電視等產品普遍發達的情況下，影像增強技術顯得越來越重要。影像即時處理以及低複雜度的設計在影像增強的考量越來越受到重視。直方圖等化（histogram equalization）是最普遍被用來實踐對比度增強的方法，然而直方圖等化有不少缺點，像是影像處理完畢後過度增強，或是有其他副作用的效果產生。為了要解決直方圖等化所造成的缺點，我們提出一個可自動調整對比度的機制伴隨著副作用的去除，以及將人眼視覺（human visual system）納入考量，如此一來我們便能有效地解決傳統直方圖等化會遇到的問題。在對比度增強過後，我們結合飽和度增強來補償對比度增強過後會出現的飽和度下降的現象。
此外，我們將演算法結合開放計算語言（Open computing language）應用在通用圖形處理器（general purpose graphic processing unit）上運算。圖形處理器上的執行緒透過分析運算相依性及平行度能夠被充分利用，記憶體配置和一些平行處理使用的技巧也被拿來使用。實驗結果證明在一般的個人電腦上運算能夠達到即時影像處理的效果。

Image enhancement has become more and more important nowadays due to the rapid progress of smart appliances such as smart phone and TV, real time processing and low complexity design have become more significant. HE (histogram equalization) is the most common way to apply contrast enhancement. However, there are not only over enhancement issue, but also lots of side effects generated after implementation on HE. In order to deal with the drawback of HE, we proposed an auto enhance level with side effect removal contrast enhancement, by taking HVS (human visual system) into consideration, we can efficiently reduce the shortcoming in conventional HE. This work combines contrast enhancement with saturation compensation while saturation drops after contrast enhancement.
Furthermore, we implement our proposed image enhancement algorithm using GPGPU (general purpose graphic processing unit) technique with OpenCL. The GPU threads are well utilized based on our analysis on execution dependency and parallelism. The device memory allocation is managed to minimize the access latency. Several parallel programming techniques are also adopted in our realization. Experimental results shows that the total processing time is dramatically improved using our methodologies, the proposed algorithm implemented in heterogeneous platform occupied real time performance when processing a Full-HD video on a modern personal computer.

[1] T. Arici, S. Dikbas, and Y. Altunbasak, “A histogram modification framework and its application for image contrast enhancement,” IEEE Trans. Image Process., vol. 18, no. 9, pp. 1921–1935, Sep. 2009.
[2] T. C. Jen and S. J. Wang, “Bayesian structure-preserving image contrast enhancement and its simplification,” IEEE Trans. Image Process., vol. 22,p. 831–843, June. 2012.
[3] D. J. Jobson, Z.-U. Rahman, and G. A. Woodell, “Properties and performance of a center/surround retinex,” IEEE Trans. Image Process., vol. 6, no. 3, pp. 451–462, Mar. 1997.
[4] D. J. Jobson, Z.-U. Rahman, and G. A. Woodell, “A multiscale retinex for bridging the gap between color images and the human observation of scenes,” IEEE Trans. Image Process., vol. 6, no. 7, pp. 965–976, July 1997.
[5] S. Aghagolzadeh and O. K. Ersoy, “Transform image enhancement,” Opt. Eng., vol. 31, no. 3, Mar. 1992, pp. 614-626.
[6] J. Tang, E. P. Peli, and S. Acton, “Image enhancement using a contrast measure in the compressed domain,” IEEE Signal Process. Lett., vol. 10, no. 10, pp. 289–292, Oct. 2003.
[7] J. Mukherjee and S. K. Mitra, “Enhancement of color images by scaling the DCT coefficients,” IEEE Trans. Image Process., vol. 17, no. 10, pp. 1783–1794, Oct. 2008.
[8] A. P. Karen., J. W. Eric, and S. Agaian, “Human visual system-based image enhancement and logarithmic contrast measure,” IEEE Trans. Systems, Man, and Cybernetics vol. 38, no. 1, pp. 174–188, Feb. 2008.
[9] Wikipedia. “HSL and HSV.” Internet: http://en.wikipedia.org/wiki/, Oct. 3 2012 [June 14, 2013].
[10] A.Choudhury and G. Medioni,” Perceptually motivated automatic color contrast enhancement” in Proc. IEEE Int. Conf. Comp. Vis. Workshop.(ICCV Workshops) Sept. 2009, pp.1893-1900.
[11] Narulasty. “更高效能更省電! 高通S4 正式發佈.” Internet: http://www.hk-android.info/archives/10298, Oct. 10, 2011 [June 14, 2013].
[12] G. Song and X. L. Qiao, “Adaptive color image enhancement based on human visual properties,” in Proc. IEEE Conf. Ind. Electron. Appl. (ICIEA), June 2008, pp. 1892-1895.
[13] C. Gao and K. Panetta, “A new color contrast enhancement algorithm for robotic applications,” in Proc. IEEE Int. Conf. Tech. for Practical Robot Appl. (TePRA), Apr. 2012, pp. 42-47.
[14] D. H. Choi , I. H. Jang , M. H. Kim ,and N. C. Kim, “Color image enhancement based on single-scale retinex with a JND-based nonlinear filter,” in Proc. IEEE Int. Symp. Circuits Syst. (ISCAS), May, 2007, pp. 3948-3951.
[15] B.R. Gaster, L. Howes, D. R. Kaeli, ”Heterogeneous Computing with OpenCL”, Elsevier Science Ltd, 2012.