Study Of Display Color Reproduction Techniques Based On Image Quality Assessment

With the improvement of industrialization and informationization level of thesociety, color display panels gradually come into life and production, and becomemain carriers from which people get information. Correct image color reproductionhas been one of the key problems that consumers and display panel manufacturerscare about. Nowadays display panels like CRT, LCD, OLED and LED display panelet al are popular, and yet because of their different color display mechanisms,cross-media image color reproduction problems exist to varying degrees. In this paper,much attention was paid on techniques in the display color reproduction workflow,and a new color reproduction algorithm based on image quality assessment wasproposed.Display panel color characterization and color gamut boundary description. Forthe color characterization of LCD、CRT and LED display panels, characterizationmathematical models were provided separately, and characterization experimentswere carried out for a LCD and LED display panel with a PR655colorimeter, andcorresponding characterization data and fitted curve were provided. After that, a fastand iterative gamut boundary calculation method for display panels was proposed.The method principle was introduced in detail, and the calculation accuracy and speedwas analyzed with LED display panel as an example. A color-characterized LED display panel cabinet whose pixel pitch was3mm was applied to verify the proposedgamut boundary description algorithm. Experiment result shows that the fittingboundary is very smooth after11iterations, and the maximum color differencebetween the true values and calculated values of gamut boundary points on everymapping line is only0.23. Compared with the interpolation methods, the maximumcolor difference is decreased and calculation speed is increased by an order ofmagnitude respectively. The algorithm could be extensively applied to other displaypanels like CRT and LCD whose color tri-stimulus and normalized lightness couledbe transformed by a characterization matrix。Quality assessment method for gamut mapping distortion images wasinvestigated. For gamut mapping distortion image, a new image quality assessmentmethod was proposed based on traditional algorithms. Firstly, both original andreproduced image are transformed into CIE LAB color space. The phase congruencyand edge strength characteristics of lightness component were extracted, and thechroma and hue difference characteristics were extracted for chroma and huecomponent, and final assessment formula named GMSIM was created based on thesefeatures. And then, being applied in3existed gamut mapping image sets and theTID2008image library, the parameters of the GMSIM algorithm were fitted, and theprediction accuracy of the algorithm was analyzed. For gamut mapping image sets, hitrate was used to indicate the algorithm performance. Experiment result shows that,compared with traditional method, the proposed GMSIM algorithm predictionaccuracy of subjective perceptions for gamut mapping distortion images wasimproved by about4.5%, although there is still much room for improvement. Theprediction performance for the TID2008image library is improved to some extent.The proposed method could be used to design new gamut mapping algorithm, and to acertain degree, it could replace the complex and time consuming subject evaluationexperiment to verify or compare the effect of different gamut mapping algorithms.Display gamut mapping based on image quality assessment. The ‘Choosingalgorithms based on image characteristics’ type gamut mapping algorithms wereintroduced in detail firstly, and then the supposed gamut mapping idea was given. After that, the characteristics of each sort of gamut mapping algorithms were analyzedand4ones were chosen as the basic algorithms. A gamut mapping algorithm namedFUSION-I was firstly provided based on GMSIM image quality assessment methodand SLIC superpixel image segmentation applying the weight map fusion idea, andwith image quality assessment results in each image segments as selection criteria,different sorts of gamut mapping algorithms were selected and comprehensivelyutilized. Color blocks could be generated using the FUSION-I method, and thusFUSION-II was provided based on the guided filtering of weight maps. Subjectiveevaluation experiments have been carried out for the provided2algorithms and other4basic gamut mapping ones, and experiment result shows that the proposedalgorithms were better than others in keeping image color fidelity, and yet the processspeed could be improved in the future.