• Science of Emotion and Sensibility
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• v.20 no.1
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• pp.57-66
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• 2017

Emotional image quality optimization methodologies are investigated using technological image quality controls based on the eye tests of various image samples. The images are evaluated based on various contrast, lightness and saturation image quality metric tone curves. The order of importance to image quality enhancements is contrast, saturation and brightness. The slopes of emotional image qualities with respect to technical image quality metric changes are found to be composed of mathematical function modelling with nearly zero, intermediate and maximum slope regions in general, which can reflect well known log and saturated as well as conventional reverse U shape natures. Image quality improvements are analyzed not only with just single but also with multiple image quality metrics. To ease the unified image quality metric analysis and control, a new function is presented to utilize both the newly found and conventional emotional image quality behaviors. It is found that the overall image quality enhancement can be realized only in a few limited cases of multiple image quality metric controls. It is also found that the kinds of image quality enhancement methodologies are not strongly dependent on image contents (genre).

• Journal of the Semiconductor & Display Technology
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• v.14 no.4
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• pp.92-97
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• 2015

The purpose of this work is to support a solution of optimizing TMO (tone mapping operator). JPEG XT Profile A and C utilize Erik Reinhard TMO that works well in most cases, however, detailed information of a scene is lost in some cases. Reinhard TMO only calculates its coefficient to have tone-mapping curve from log-average luminance, and this lead to lose details of bright and dark area of scenes in turn. Thus, this paper proposes an enhancement of the default TMO for JPEG XT Profile C to optimize tone-mapping curve. Main idea is that we divide tone mapping curve into several ranges, and set reasonable parameters for each range. By the experimental results, the proposed scheme shows and obtains better performance within a dark scene, compared to the default Reinhard TMO.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.45 no.2
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• pp.65-73
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• 2008

The characterization process for the accurate color reproduction in mobile phone with camera and LCD is popular. The camera and LCD characterization, gamut mapping process is necessary to map the camera's input color stimulus, CIEXYZ value, into the LCD's output color stimulus. Each characterization is the process estimating the relation between input and output signals. In case of LCD, because of output device, the output color stimulus for the arbitrary input signal can be measured by spectro-radiometer However, in the camera, as the input device, the characterization is an inaccurate and needs the manual works in the process obtaining the output signal because the input signal can not be generated. Moreover, after gamut mapping process, the noise is increased because the optimized gamma tone curve of camera for the noise is distorted by the characterization. Thus, this paper proposed the system of obtaining the output signal of camera and the method of gamma correction for the noise. The camera's output signal is obtained by RGB values of patches from captured the color chart image. However, besides the illumination, the error for the location of the chart in the viewfinder is generated when many camera modules are captured the chart. The method of correcting the position to correct the error from manual works. The position of camera is estimated by captured image. This process and moving of camera is accomplished repeatedly, and the optimized position can be obtained. Moreover, the lightness curve of camera output is corrected partly to reduce the noise from the characterization process.