• Proceedings of the KIEE Conference
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• 2000.07d
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• pp.2921-2923
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• 2000

Adaptive template filtering has been proposed recently for an enhancement of signal-to-noise ratio. In some magnetic resonance images whose gray levels have relatively small dynamic ranges, e.g., T1 imaging, however, artificial stair-like artifact is observed in edge regions. This is partially due to edge enhancement effect in such voxels that contain multiple compounds at the boundaries of tissues. The gray levels of these voxels tend to change those of near voxels that contain single compound by the adaptive filtering, which exaggerate edge discontinuities. In this paper, we propose a technique to eliminate such artifact by identifying those voxels and assigning a larger template for them. Filtered images with the proposed technique show substantial visual enhancement at the edges without degradation of peak signal-to-noise ratio compared to the original adaptive template filtering for both magnetic resonance images and phantom images

• Journal of Biomedical Engineering Research
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• v.17 no.4
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• pp.427-432
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• 1996

The primary purpose of port filming is to verify the treatment volume under treatment. Although the image quality with the megavoltage x-ray beam is poorer than with the diagnostic or the simulator film. This paper proposes an edge-adaptive Kalman filter for the image enhancement of port films. Suggested filtering procedure preserves edge information and eliminates edge noise and inside and outside treatment area preserving treatment boundary.

• Journal of the Institute of Convergence Signal Processing
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• v.9 no.4
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• pp.288-294
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• 2008

In this paper, we proposed an algorithm of edge enhancement to improve image visibility of mobile phone camera. For naturally edge enhancement, we grasps edge characteristic in image and applied to the most appropriate enhancement value adaptively about each characteristics. Namely, It applies 2D high pass filter where in the edge characteristics which judge in the first In compliance with the edge condition which is subdivided more with secondary it will be able to apply the process which able to adaptive edge enhancement to improve image visibility. It joins in and it is an existing algorithm that simply a lies 2D high pass filter where and it is identical in the image whole it will be able to improve the side effects of ringing actual condition etc. It considers the effectiveness of the hardware resource with the hardware of the algorithm which is developed and algorithm the maximum simply, it developed and simulation of the algorithm which is proposed it led and algorithm of existing and it compared and is improved the result which it confirmed.

• Journal of the Korea Society of Computer and Information
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• v.21 no.11
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• pp.23-30
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• 2016

In this paper, we propose an adaptive histogram projection technique for dynamic range compression and an efficient detail enhancement method which is enhancing strong edge while reducing noise. First, The high dynamic range image is divided into low-pass component and high-pass component by applying 'guided image filtering'. After applying 'guided filter' to high dynamic range image, second, the low-pass component of the image is compressed into 8-bit with the adaptive histogram projection technique which is using global standard deviation value of whole image. Third, the high-pass component of the image adaptively reduces noise and intensifies the strong edges using standard deviation value in local path of the guided filter. Lastly, the monitor display image is summed up with the compressed low-pass component and the edge-intensified high-pass component. At the end of this paper, the experimental result show that the suggested technique can be applied properly to the IR images of various scenes.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.43 no.1 s.307
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• pp.9-16
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• 2006

This Paper proposes an adaptive error diffusioThis paper proposes an adaptive error diffusion algorithm for text enhancement followed by an efficient text segmentation that uses the maximum gradient difference (MGD). The gradients are calculated along with scan lines, and the MGD values are filled within a local window to merge the potential text segments. Isolated segments are then eliminated in the non-text region filtering process. After the left segmentation, a conventional error diffusion method is applied to the background, while the edge enhancement error diffusion is used for the text. Since it is inevitable that visually objectionable artifacts are generated when using two different halftoning algorithms, the gradual dilation is proposed to minimize the boundary artifacts in the segmented text blocks before halftoning. Sharpening based on the gradually dilated text region (GDTR) prevents the printing of successive dots around the text region boundaries. The error diffusion algorithm with edge enhancement is extended to halftone color images to sharpen the tort regions. The proposed adaptive error diffusion algorithm involves color halftoning that controls the amount of edge enhancement using a general error filter. The multiplicative edge enhancement parameters are selected based on the amount of edge sharpening and color difference. Plus, the additional error factor is introduced to reduce the dot elimination artifact generated by the edge enhancement error diffusion. By using the proposed algorithm, the text of a scanned image is sharper than that with a conventional error diffusion without changing background.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.15 no.1
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• pp.35-44
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• 2015

The main purpose of image enhancement is to improve certain characteristics of an image to improve its visual quality. This paper proposes a method for image contrast enhancement that can be applied to both medical and natural images. The proposed algorithm is designed to achieve contrast enhancement while also preserving the local image details. To achieve this, the proposed method combines local image contrast preserving dynamic range compression and contrast limited adaptive histogram equalization (CLAHE). Global gain parameters for contrast enhancement are inadequate for preserving local image details. Therefore, in the proposed method, in order to preserve local image details, local contrast enhancement at any pixel position is performed based on the corresponding local gain parameter, which is calculated according to the current pixel neighborhood edge density. Different image quality measures are used for evaluating the performance of the proposed method. Experimental results show that the proposed method provides more information about the image details, which can help facilitate further image analysis.

• Investigative Magnetic Resonance Imaging
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• v.4 no.2
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• pp.120-127
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• 2000

Adaptive template filtering has been proposed recently for enhancement of signal-to-noise ratio without loss of resolution. In the adaptive template filtering, an optimal template among multiple templates is selected, then linear least square error filtering based on the template is applied in vowel by vowel basis. In some magnetic resonance imaging, where the distribution of gray level has relatively small dynamic range, e.g., $T_1$ imaging, however, artificial stair-like artifact is observed at near edges. This is partially due to the edge enhancement effect in such yokels that contain multiple compounds at the boundaries of tissues. The gray levels of these yokels become similar gray levels of near dominant vowels that contain single compound by the adaptive filtering, which enlarges edge discontinuities. In this paper, we propose a technique to eliminate such artifact by identifying those yokels that contain multiple compounds and assigning the largest template for them. Filtered images with the proposed technique show substantial visual enhancement at the edges without degradation of peak signal-to-noise ratio compared to the original adaptive template filtering for both magnetic resonance images and phantom images.

• Journal of the Korea Society of Computer and Information
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• v.16 no.3
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• pp.27-34
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• 2011

In this paper, the novel approach for image contrast enhancement is introduced. The method is based on the unsharp mask and directional information of images. Since the unsharp mask techniques give better visual quality than the conventional sharpening mask, there are much works on image enhancement using unsharp masks. The proposed algorithm decomposes the image to several blocks and extracts directional information using DCT. From the geometric properties of the block, each block is labeled as appropriate type and processed by adaptive unsharp mask. The masking process is skipped at the flat area to reduce the noise artifact, but at the texture and edge area, the adaptive unsharp mask is applied to enhance the image contrast based on the edge direction. Experiments show that the proposed algorithm produces the contrast enhanced images with superior visual quality, suppressing the noise effects and enhancing edge at the same time.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.11 no.2
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• pp.33-42
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• 2003

In this paper, we propose an enhancement of the ultrasonic image for non-destructive inspection of aircraft composite materials. The ultrasonic images are corrupted by a speckle noise which has the characteristic of granular pattern noise and is in all types of coherent imaging systems, the signal independent and multiplicative noise. In this paper, we derive a filter, called the AWLF(Adaptive Window Log Filter), from the nature of the speckle. The filter is made of the MEAN Filter in the edge region and Log Filter in the flat or noise region. To make a distinction between edge and flat region, we calculate the inclination around the local window instead of computing the local statistics of pixels such as local mean ${\bar{M}}$ and standard deviation ${\sigma}_s$. According to the obtained region, edge region is performed by the mean filter and flat region by the Log filter. Performance of the proposed filter is evaluated by the Enhanced Factor$(F_e)$ and the Speckle Index(SI).

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.1
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• pp.658-665
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• 2015

In the production of medical images, noise reduction and contrast enhancement are important methods to increase qualities of processing results. By using the edge-based denoising and adaptive nonlinear histogram stretching, a novel medical image enhancement algorithm is proposed. First, a medical image is decomposed by wavelet transform, and then all high frequency sub-images are decomposed by Haar transform. At the same time, edge detection with Sobel operator is performed. Second, noises in all high frequency sub-images are reduced by edge-based soft-threshold method. Third, high frequency coefficients are further enhanced by adaptive weight values in different sub-images. Finally, an adaptive nonlinear histogram stretching method is applied to increase the contrast of resultant image. Experimental results show that the proposed algorithm can enhance a low contrast medical image while preserving edges effectively without blurring the details.