• Journal of Broadcast Engineering
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• v.16 no.3
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• pp.552-560
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• 2011

In this paper, a new no-reference sharpness measure using frequency domain coefficients is proposed. Although most existing sharpness measures used pixel intensity to compute the blur degree, the proposed sharpness measure computes the sharpness using frequency coefficients. To assess the perceived sharpness of a given image, the image is re-blurred by a Gaussian low pass filter and a new quality measure function was defined using the frequency domain coefficients of the given image and the re-blurred image. To evaluate the proposed algorithms, TID2008 quality assessment database was used. Experimental results show that the proposed quality assessment method showed high correlation with the subjective scores.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.4
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• pp.127-136
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• 2013

This paper proposes a video deblurring algorithm which maintains uniform sharpness between frames. Unlike the previous algorithms using fixed parameters, the proposed algorithm keeps uniform sharpness by adjusting parameters for each frame. First, we estimate the initial blur kernel and perform deconvolution, then measure the sharpness of the deblurred image. In order to maintain uniform sharpness, we adjust the regularization parameter and kernel according to the examined sharpness, and perform deconvolution again. The experimental results show that the proposed algorithm achieves outstanding deblurring results while providing consistent sharpness.

• IEIE Transactions on Smart Processing and Computing
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• v.5 no.6
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• pp.390-394
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• 2016

This paper presents a new comparison method for haze-removal algorithms in next-generation automotive systems. Compared to previous peak signal-to-noise ratio-based comparisons, which measure similarity, the proposed modulation transfer function-based method checks sharpness to select a more suitable haze-removal algorithm for lane detection. Among the practical filtering schemes used for a haze-removal algorithm, experimental results show that Gaussian filtering effectively preserves the sharpness of road images, enhancing lane detection accuracy.

• Journal of Broadcast Engineering
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• v.12 no.4
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• pp.350-359
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• 2007

In this paper we present a simple, efficient method for detection of sharp digital images. Recently many digital cameras are equipped with various autofocusing functions to help users take well-focused pictures as easily as possible. However, acquired digital pictures can be further degraded by motion, limited contrast, and inappropriate amount of exposure, to name a few. In order to decide whether to process the image or not, or whether to delete it or not, reliable measure of image quality to detect sharp images from blurry ones is needed. This paper presents a blurriness/sharpness measure, and demonstrates its feasibility using extensive experiments. This method is fast and easy to implement, and accurate. Regardless of the detection accuracy, existing measures are computation-intensive. However, the proposed measure in this paper is not demanding in computation time. Needless to say, this measure can be used for various imaging applications including autofocusing and astigmatism correction.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.49 no.4
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• pp.32-39
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• 2012

This paper develops a robust image enhancement method by adjusting image signal energy according to the direction and the variation of image signal in DCT domain. To accomplish this, we measure the gradient of image signal directly in DCT domain and then adjust frequency components involved in sharpness, local contrast and global contrast using the direction and the magnitude of the measured gradient The experiment showed that the proposed method produces the best quality of an image without causing blocking, ringing artifacts and boosting noise.

• Journal of the Semiconductor & Display Technology
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• v.19 no.3
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• pp.7-11
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• 2020

Enormous methods have been proposed for the detection and segmentation of blur and non-blur regions of the images. Due to the limited available information about the blur type, scenario and the level of blurriness, detection and segmentation is a challenging task. Hence, the performance of the blur measure operators is an essential factor and needs improvement to attain perfection. In this paper, we propose an effective blur measure based on the local binary pattern (LBP) with the adaptive threshold for blur detection. The sharpness metric developed based on LBP uses a fixed threshold irrespective of the blur type and level which may not be suitable for images with large variations in imaging conditions and blur type and level. Contradictory, the proposed measure uses an adaptive threshold for each image based on the image and the blur properties to generate an improved sharpness metric. The adaptive threshold is computed based on the model learned through the support vector machine (SVM). The performance of the proposed method is evaluated using a well-known dataset and compared with five state-of-the-art methods. The comparative analysis reveals that the proposed method performs significantly better qualitatively and quantitatively against all the methods.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2006.11a
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• pp.31-34
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• 2006

• Current Optics and Photonics
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• v.8 no.2
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• pp.170-182
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• 2024

The dimensional accuracy and consistency of a dual oil circuit centrifugal fuel nozzle are important for fuel distribution and combustion efficiency in an engine combustion chamber. A point cloud measurement method was proposed to solve the geometric accuracy detection problem for the fuel nozzle. An improved variance focus measure operator was used to extract the depth point cloud. Compared with other traditional sharpness evaluation functions, the improved operator can generate the best evaluation curve, and has the least noise and the shortest calculation time. The experimental results of point cloud slicing measurement show that the best window size is 24 × 24 pixels. In the height measurement experiment of the standard sample block, the relative error is 2.32%, and in the fuel nozzle cone angle measurement experiment, the relative error is 2.46%, which can meet the high precision requirements of a dual oil circuit centrifugal fuel nozzle.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.45 no.6
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• pp.88-94
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• 2008

A DCT-based energy-ratio measure for autofocus in digital camera is proposed in this paper. This measure, namely AC2DC1 and AC5DC1, determines the sharpness of an image using a ratio between AC and DC energy in the DCT domain. This method is derived from energy analysis of DCT coefficients. Autofocus score calculation method is used to assess the performance of the proposed measure and to compare it with other measures. Experimental results under various conditions verify the robustness of the proposed focus measure for the Gaussian as well as impulsive noises.

• Journal of The Korean Astronomical Society
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• v.55 no.4
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• pp.87-97
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• 2022

Polarimetric measurements of the lunar surface from lunar orbit soon will be available via Wide-Field Polarimetric Camera (PolCam) onboard the Korea Pathfinder Lunar Orbiter (KPLO), which is planned to be launched in mid 2022. To provide calibration data for the PolCam, we are conducting speckle polarimetric measurements of the nearside of the Moon from the Earth's ground. It appears that speckle imaging of the Moon for scientific purposes has not been attempted before, and there is need for a procedure to create a "lucky image" from a number of observed speckle images. As a first step of obtaining calibration data for the PolCam from the ground, we search for the best sharpness measure for lunar surfaces. We then calculate the minimum number of speckle images and the number of images to be shift-and-added for higher resolution (sharpness) and signal-to-noise ratio.