Liquid-crystal displays (LCDs) with different types of surface treatment have been developed for decreasing the effect of ambient lighting on a displayed image. The effect of ambient lighting on LCDs with different surface treatments, namely, glare (G)-type, anti-glare (AG)-type, and anti-reflection (AR)-coating LCDs, was evaluated quantitatively in this study for appropriate selection. The effect of ambient lighting on diffuse reflection and specular reflection was investigated. The coefficient of diffuse reflection of the AR-coating LCD was smaller than the others. The effect of diffuse reflection on the display function of each LCD was evaluated in terms of the deviation of the contrast response at the lowest luminance level when the illuminance changed from the condition that was used for calibration of the grayscale standard display function. The display function of the AR-coating LCD was affected less by diffuse reflection compared to the others. On the other hand, the coefficient of specular reflection of the AG-type LCD was the smallest until the angle of aperture of the light source was 4.6°. The specular-reflected image on the AG-type LCD had a remarkably broad distribution compared to the others. Our results are merely examples for a limited number of LCDs; however, we clarified quantitatively that the AR-coating and the AG-type LCDs were affected less by diffuse and specular reflection than the G-type LCD.
Purpose:
To develop a method for improving sharpness of images reproduced on liquid‐crystal displays (LCDs) by compensating for the degradation of modulation transfer function (MTF) of the LCD.
Methods:
The inherent MTF of a color LCD (display MTF) was measured using a commercially available color digital camera. The frequency responses necessary to compensate for the resolution property of the LCD were calculated from the inverses of the display MTFs in both the horizontal and vertical directions. In addition, the inverses of the display MTFs were combined with the response of the human eye. The finite impulse response (FIR) filters were computed by taking the inverse Fourier transform of the frequency responses, and the effects of the FIR filtering on both the resolution and noise properties of the displayed images were verified by measuring the MTF and Wiener spectrum (WS), respectively. The FIR filtering was then applied to the representation of digital bone and chest radiographs.
Results:
The FIR filtering improved the MTF values by up to almost 1.0 or greater over the frequency range of interest, while it minimally increased the WS values. Combining the inverses of the display MTFs with the response of the human eye led to further refinement of the MTF. Our method was successfully and beneficially applied to the image interpretation of bone radiographs. The resolution enhancement of chest radiographs, which include larger scattered radiation than bone radiographs, was easily perceived by incorporating the response of the human eye. In addition, no artifacts were observed on the processed images.
Conclusion:
Our proposed method to compensate for the degradation of the resolution properties of LCDs has the potential to improve the observer performance of radiologists when reading digital radiographs.
This work was supported in part by grant from EIZO Corporation.
We developed a simplified tool for measuring image quality of medical liquid-crystal displays (LCDs) using a commercially available color digital camera. This tool implemented as a plug-in software for ImageJ (open-source image processing program) was designed to compute modulation transfer functions (MTFs) and Wiener spectra (WS) of monochrome and color LCDs from LCD photographed images captured by a camera. The intensities of the red (R), green (G), and blue (B) signals of the unprocessed image data depend on the spectral sensitivity of the image sensor used in the camera. In order to evaluate image quality based on LCD luminance, the plug-in software calibrates the RGB signals from the camera using measured luminance of the LCD and converts them into grayscale signals that correspond to the luminance of the LCD. The MTFs and WS are determined based on the line response from a one-pixel line image and the one-dimensional noise profiles acquired by scanning the uniform image using numerically synthesized slit, respectively. With this plug-in software for ImageJ, we are able to readily compute MTFs and WS of both monochrome and color LCDs from unprocessed image data of cameras. Our simplified tool is helpful to evaluate and understand the physical performance of LCDs for a large number of display users in hospitals and medical centers.
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