• Journal of Korea Multimedia Society
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• v.16 no.10
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• pp.1180-1188
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• 2013

Interpolation or super-resolution is used in order to restore degradation of image quality that appears after various transform of image. The method on subjective or objective image resolution improvement having low computation complexity has been being researched in many different ways. In this paper, image enhancement method using improved self degradation restoration(ISDR) method is proposed. The proposed method uses ISDR to estimate pixel value of missed coordinate in the process of image scaling, and combines the estimated loss information and interpolated image to generate enhanced result image. The proposed method shows that PSNR increases by 1.8dB, and subjective image quality is superior to other compared methods. The proposed method can be applied as a basis technique in variety of applications which requires image scale transform.

• Journal of the Institute of Convergence Signal Processing
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• v.5 no.4
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• pp.271-280
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• 2004

This paper presents a new iterative image restoration algorithm with removal of boundary/object-oriented ringing, The proposed method is based on CGM(Conjugate Gradient Method) iterations with inter-wavelet shrinkage. The proposed method provides a fast restoration as much as CGM, while having adaptive do-noising and do-ringing by using wavelet shrinkage. In order to have effective do-noising and do-ringing simultaneously, the proposed method uses a space-dependent shrinkage rule. The improved performance of the proposed method over more traditional iterative image restoration algorithms such as LR(Lucy-Richardson) and CGM in do-noising and do-ringing is shown through numerical experiments.

• Journal of the Korea Computer Industry Society
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• v.6 no.3
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• pp.447-456
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• 2005

This paper describes iterative restoration method of restoring blurred images using the LOG compansion function and Conjugate Gradient method. Conventional restoration methods results satisfy the requirement performance for restoring blurred images. but iteration number and convergence velocity increase. This paper proposed an opmtimised iteration restoration method for the images degraded by blurring effect, using the LOG compansion function and Conjugate Gradient method. Here, the LOG compansion function used to improve local properties of the image being restored, made the visual character and convergence velocity of the restored image improved. Throught the simulation results, the author showed that proposed algorithm produced superior performance results by conventional methods.

• Transactions of the Society of Information Storage Systems
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• v.5 no.1
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• pp.36-40
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• 2009

We describe the experimental realization of image system using wavefront coding in 3-Mega pixel mobile phone camera. We designed aspheric lens to extend the depth of field (DOF) using wavefront coding. In addition, through the aspheric lens and lens barrel manufacturing, we obtained a raw image from a camera module. In our method, the acquired images are restored in the spatial frequency domain using the proposed filter and the spatial frequency response (SFR) is calculated. The proposed filters are composed of image denoising filter using low band pass filter in frequency domain and restoration filter for image restoration. Finally, we achieve an enhanced image by super-resolution image processing. Visual examples are given to demonstrate the performance of the proposed filter.

• Proceedings of the Korea Society for Industrial Systems Conference
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• 1997.11a
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• pp.91-101
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• 1997

The demand for handling images in digital form has increased dramatically in recent years. Digital image compression is required to store and transmit mass information in different from general information. JPEG(Joint Photographic Experts Group) committee founded by CCITT and ISO is define the still-image standard compression/restoration algorithm. JPEG is proposed the standard of grayscale and color still-image compression/restoration. In the image quality, JPEG is applicable to the various applications in which compression is able to from 1/10 to 1/50 without the visible obstacle. In this paper, we proposed that the proposed method enhance the compression ratio which is reducing the higher frequency in order to increasing the spatial redundancy in the image. The proposed method is using the low pass filter in order to reducing the higher frequency. The low-pass filters are using the median filter and convolution filter in the spatial domain, FFT filter in the frequency domain. We acquired the additive compression ratio reducing the higher frequency using the low-pass filter.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.4 no.2
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• pp.117-137
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• 2010

Iris recognition is a biometric technique which uses unique iris patterns between the pupil and sclera. The advantage of iris recognition lies in high recognition accuracy; however, for good performance, it requires the diameter of the iris to be greater than 200 pixels in an input image. So, a conventional iris system uses a camera with a costly and bulky zoom lens. To overcome this problem, we propose a new method to restore a low resolution iris image into a high resolution image using a single image. This study has three novelties compared to previous works: (i) To obtain a high resolution iris image, we only use a single iris image. This can solve the problems of conventional restoration methods with multiple images, which need considerable processing time for image capturing and registration. (ii) By using bilinear interpolation and a constrained least squares (CLS) filter based on the degradation model, we obtain a high resolution iris image with high recognition performance at fast speed. (iii) We select the optimized parameters of the CLS filter and degradation model according to the zoom factor of the image in terms of recognition accuracy. Experimental results showed that the accuracy of iris recognition was enhanced using the proposed method.

• Journal of Broadcast Engineering
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• v.19 no.1
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• pp.109-117
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• 2014

This paper presents a superresolution restoration technique that can restore high-resolution images from differently blurred low resolution images rather than using the motion information between low-resolution images. In order to restore the super-resolution image the rotatable aperture mask lens system is proposed. The proposed technique does not need to estimate point spread function at each frame. In addition, it does not require image registration because there is no global translational motion between low resolution images. By using a rotatable rectangular aperture, two consecutive captured images provide sufficiently exclusive information for superresolution. Therefore, the proposed method can reduce the registration error between the low-resolution image as well as the calculation amount for superresolution restoration. The existing lens system of the camera can be extended to obtain a superresolution image by only adding an rotatable rectangular aperture mask. Finally, in order to verify the performance of the proposed system, experimental results are performed. By comparing with the existing superresolution methods, the proposed method showed the significant improvements in the sense of spatial resolution.

• Journal of information and communication convergence engineering
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• v.9 no.3
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• pp.331-335
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• 2011

Digital images are often corrupted by impulse noise, and it is very important to remove random-valued impulse noise. Cleaning such noise is far more difficult than cleaning salt and pepper impulse noise. In this paper, we proposed an efficient way to remove random-valued impulse noise from digital images. This novel method comprises two stages. The first stage is to detect the random-valued impulse noise in the image and the pixels are roughly divided into two classes, which are "noise-free pixel" and "noise pixel". Then, the second stage is to eliminate the random-valued impulse noise from the image. In this stage, only the "noise pixels" are processed. The "noise-free pixels" are copied directly to the output image. Simulation results indicated that our method provides a significant improvement over many other existing algorithms.

• Proceedings of the KSRS Conference
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• 2008.10a
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• pp.365-367
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• 2008

A digital city model represents a 3D environment of a city with various city object information such as 3D building model, road, and land cover. Usually, at least two satellite images with some image overlap are necessary and a complex satellite-related computation needs to be carried out to create a city model. This is an expensive technique, because it requires many resources and excessive computational cost. The authors propose a methodology to create a digital city model including 3D building model and land cover information from a single high resolution satellite image. The approach consists of image pan-sharpening, shadow recovery, building occlusion restoration, building model extraction, and land cover classification. We create a digital city model using a single KOMPSAT-2 image and review the result.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.47 no.5
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• pp.145-152
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• 2010

This paper presents a digital auto-focusing algorithm using iterative unsharp mask filter. The proposed digital auto-focusing algorithm has the advantage of low computational complexity because it uses a simple filter instead of calculating the point spread function for the estimation of image degradation. The proposed iterative algorithm can control the number of iterations for image restoration according to the objective and the subjective criterion. We show that the proposed algorithm is mathematically equivalent to the conventional image restoration. Finally, in order to evaluate the performance of the proposed algorithm, various experiments are performed so that the proposed algorithm can provide good results in the sense of subjective and objective views.