• Journal of Biomedical Engineering Research
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• v.37 no.4
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• pp.140-146
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• 2016

The ultrasound imaging in medical diagnosis has become a popular modality because of its safe, noninvasive, portable, relatively inexpensive, and provides a real-time image formation. However, usefulness of ultrasound imaging is at times limited due to the presence of signal-dependent noise like as speckle. Therefore, noise reduction is very important, as various types of noise generated limits the effectiveness of medical image diagnosis. This paper introduces a speckle noise reduce algorithm using total variation denoising (TVD) in Laplacian pyramid. With this method, speckle is removed by TVD of bandpass ultrasound images in Laplacian pyramid domain. For TVD in each pyramid layer, a ${\lambda}$ is selected by trial-and-error method. The visual comparison of despeckled 'in vivo' ultrasound images from pancreas shows that the proposed method could effectively preserve edges and detailed structures while thoroughly suppressing speckle. For a Simulated B-mode image, contrast-to-noise-ratio (CNR) and signal-to-noise-ratio (SNR) were obtained like 4.65 dB and 14.11 dB, respectively. The results show that the proposed method can conduct better than some of the existing methods in terms of the CNR and the SNR.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38A no.11
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• pp.928-937
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• 2013

This paper presents a novel contrast enhancement method based on singular value decomposition and image pyramid. The proposed method consists mainly of four steps. The proposed algorithm firstly decomposes image into band-pass images, including basis image and detail images, to improve both the global contrast and the local detail. In the global contrast process, singular value decomposition is used for contrast enhancement; the local detail scheme uses weighting factors. In the final image composition process, the proposed algorithm combines color and luminance components in order to preserve the color consistency. Experimental results show that the proposed algorithm improves contrast performance and enhances detail compared to conventional methods.

• Journal of IKEEE
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• v.26 no.2
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• pp.292-298
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• 2022

There is a limit to improving the image quality through global processing of images taken under backlighting because too bright and dark parts are mixed in one scene. This paper introduces a method to improve the quality of a photo by making two virtual images that improve the dark and bright areas of a backlit photo, and fusing them with the original image into a Laplacian pyramid. The proposed method reduces the computational burden by using histogram stretching and gamma transformation that can be simplified with LUT when creating the two virtual images. In addition, in order to obtain a color-enhanced image, contrast conversion was performed only on the luminance using the HSV coordinate system. The proposed technique showed its effectiveness by calculating several NIQA indicators using standard image data sets.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.15 no.2
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• pp.137-146
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• 1990

A series of images whose sized and resolutions differ by a constant factor are called an image pyramid. Because the images at high levels are small, large object can be detected on high levels of the pyramid at low cost, But in this way, the boundaries of objects are not accurately localized. Therefore the pyramid algorithms extracte the objects by segmentation the constructed image using bottom-up method and description it in an original resolution using inverse bottom-up method. In this paper, we can project an object down to the next lower level of the pyramid and apply to the boundary adjustment algorithm at that level to localize it more precisely. We repeat the process at successively lower levels. In this paper, we present a method of boundary adjustment using an image pyramid to obtain optimal boundary. The performance of the proposed algorithm is compared to those of the conventional method in term of subjective quality of object boundary.

• Journal of Broadcast Engineering
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• v.1 no.2
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• pp.165-175
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• 1996

In this paper, the image segmentation method based on the hierarchical pyramid image structure of reduced resolution versions of the image for solving the problems in the conventional methods is presented. This method is described the object detection and delineation by statistical approach. In the object detection method, IFSVR( Inverse-father-son variance ratio) method and FSVR(father-son variance ratio ) method are proposed for solving clustering validity problem occurred In the hierarchical pyramid image structure. An optimal object pixel Is detected at some level by this method. In the object delineation method, the iterative algorithm by top-down traversing method is proposed for moving the optimal object pixel to levels of higher resolution. Using the computer simulation, the results by the proposed statistical methods and object traversing method are investigated for the binary Image and the real image. At the results of computer simulation, the proposed methods of image segmentation based on the hierarchical pyramid Image structure seem to have useful properties and deserve consideration as a possible alternative to existing methods of image segmentation. The computation for the proposed method is required 0(log n) for n${\times}$n input image.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.3
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• pp.1182-1194
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• 2016

The single image dehazing algorithm in existence can satisfy the demand only for improving either the effectiveness or efficiency. In order to solve the problem, a novel variational framework for single image dehazing based on restoration is proposed. Firstly, the initial atmospheric scattering model is transformed to meet the kimmel's Retinex variational model. Then, the green light component of image is considered as an input of the variational framework, which is generated by the sensitivity of green wavelength. Finally, the atmospheric transmission map is achieved by multi-resolution pyramid reduction to improve the visual effect of the results. Experimental results demonstrate that the proposed method can remove haze effectively with less memory consumption.

• Journal of Multimedia Information System
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• v.5 no.2
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• pp.87-90
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• 2018

Various approaches have been proposed to convert low dynamic range (LDR) to high dynamic range (HDR). Of these approaches, the Multi Scale Fusion (MSF) algorithm based on Laplacian pyramid decomposition is used in many applications and demonstrates its usefulness. However, the pyramid fusion technique has no means for controlling the luminance component because the total number of pixels decreases as the pyramid rises to the upper layer. In this paper, we extract the reflection light of the image based on the Retinex theory and generate the weight map by adjusting the reflection component. This weighting map is applied to achieve an MSF-like effect during image fusion and provides an opportunity to control the brightness components. Experimental results show that the proposed method maintains the total number of pixels and exhibits similar effects to the conventional method.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.40 no.2
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• pp.1-10
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• 2003

This paper presents an efficient method for image segmentation based on a multiresolution application of a wavelet transform and watershed segmentation algorithm. The procedure toward complete segmentation consists of four steps: pyramid representation, image segmentation, region merging and region projection. First, pyramid representation creates multiresolution images using a wavelet transform. Second, image segmentation segments the lowest-resolution image of the pyramid using a watershed segmentation algorithm. Third, region merging merges the segmented regions using the third-order moment values of the wavelet coefficients. Finally, the segmented low-resolution image with label is projected into a full-resolution image (original image) by inverse wavelet transform. Experimental results of the presented method can be applied to the segmentation of noise or degraded images as well as reduce over-segmentation.

• Proceedings of the IEEK Conference
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• 2000.06d
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• pp.210-213
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• 2000

In the closed range space, the parallel two CCD cameras are used to acquire a pair of stereo image. The acquired stereo image are computed with Wavelet Transform repeatedly and including the low frequency component, the image size of those are reduced. It is the pyramid structure. The optimum matching point is searched to the pixel. Then appling the optimum matching point to DLT, it extract the three - dimensional surface coordinate from a stereo image. The direct linear transformation(DLT) method is used to calibrate the stereo camera compute the coordinate on a three dimensional space. To find the parameters for the DLT method, 30 control points which marked on the cylinder type object are used. To improve the matching algorithm, the paper select the pyramid structure for Wavelet Transform. The acquired disparity information is used to represent the really three-dimensional surface coordinate.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.5
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• pp.1761-1777
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• 2021

An image with infrared features and visible details is obtained by processing infrared and visible images. In this paper, a fusion method based on Laplacian pyramid and generative adversarial network is proposed to obtain high quality fusion images, termed as Laplacian-GAN. Firstly, the base and detail layers are obtained by decomposing the source images. Secondly, we utilize the Laplacian pyramid-based method to fuse these base layers to obtain more information of the base layer. Thirdly, the detail part is fused by a generative adversarial network. In addition, generative adversarial network avoids the manual design complicated fusion rules. Finally, the fused base layer and fused detail layer are reconstructed to obtain the fused image. Experimental results demonstrate that the proposed method can obtain state-of-the-art fusion performance in both visual quality and objective assessment. In terms of visual observation, the fusion image obtained by Laplacian-GAN algorithm in this paper is clearer in detail. At the same time, in the six metrics of MI, AG, EI, MS_SSIM, Q_abf and SCD, the algorithm presented in this paper has improved by 0.62%, 7.10%, 14.53%, 12.18%, 34.33% and 12.23%, respectively, compared with the best of the other three algorithms.