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As medical images are mostly fuzzy in nature, segmenting regions based intensity is the most challenging task. Segmentation of medical images using seeded region growing technique is increasingly becoming a popular method because of its ability to involve high-level knowledge of anatomical structures in seed selection process. In this paper, we have made improvements in region growing image segmentation...
In this paper, we propose a non-symmetry and anti-packing image representation model (NAM). NAM is a hierarchical image representation method and its aim is less data amount and faster operation. By taking a rectangle sub-pattern for example, we describe the idea of NAM. In addition, an approach for adaptive area histogram equalization image contrast enhancement based on a NAM image is presented....
The video sequences degraded by fog suffer from poor visibility. In this paper, we present a contrast limited adaptive histogram equalization (CLAHE)-based method to remove fog. CLAHE establishes a maximum value to clip the histogram and redistributes the clipped pixels equally to each gray level. It can limit the noise while enhancing the contrast. First, the background image is extracted from the...
A fracture is a crack or break in the bone. This can be easily detected by taking an X-ray in that area. But some times these images lack sufficient brightness. Various Equalization Methods can be adapted to enhance the image. In this paper, two such methods are compared. They are Histogram Equalization and Contrast Limited Adaptive Histogram Equalization. The results show that Contrast Limited Adaptive...
As for the halo and noise which partly appear too bright or dark in the DR (digital radiography), an improved algorithm of contrast limited histogram equalization is presented in this paper. And it is based on a number of image enhancement algorithm experiments. After enhancing the images collected from different body parts, the algorithm proves to effectively inhibit halo emergence. In addition,...
The images degraded by fog suffer from poor contrast. In order to remove fog effect, a Contrast Limited Adaptive Histogram Equalization (CLAHE)-based method is presented in this paper. This method establishes a maximum value to clip the histogram and redistributes the clipped pixels equally to each gray-level. It can limit the noise while enhancing the image contrast. In our method, firstly, the original...
This paper presents the adaptive histogram adjustment (AHA) to improve image contrast. The proposed method is achieved based on the concepts of weighted histogram separation and gray-level grouping. It not only improves the contrast of the local detail but also solves group density and blocky effect which occur at the under-quantization problem of weighted histogram separation. Moreover, the adaptive...
This paper presents a novel feature extraction method using the combination of the Coordinate Logic Filters (CLF) and Artificial Neural Networks (ANN) applied to 2D signals (Images). The method consists of image enhancement by histogram adaptive equalization technique, features extraction by modifying gray levels applying a nonlinear adaptive transformation function and edge detection by Coordinate...
The technologies for image contrast enhancement are improved evidently since the popularity of consumer electronics and image processing in the last decade. Based on histogram equalization (HE), this paper proposes a simple contrast enhancement scheme named adaptively increasing the value of histogram (AIVHE). It provides a convenient and effective mechanism to control the rate of contrast enhancement...
lambda-enhancement, introduced by Tizhoosh et al., is a contrast adjustment technique that uses involutive fuzzy complements to find the best gray-level transformation in order to increase the image contrast. Applied on medical images, lambda-enhancement can provide good results with respect to visually perceived improvement of object-background discrimination. In this work, we provide two extensions...
In this paper we propose a novel image contrast enhancement method using collaborative learning. Block-based histogram equalization methods such as contrast limited adaptive histogram equalization (CLAHE) and exact histogram equalization consider only a local window or neighboring windows for contrast enhancement. Inspired by the collaborative learning of individuals in a knowledge-creating community,...
Image enhancement is a useful technique to improve the visual appearance of an image by removing noise, improving contrast of an image, smoothing, sharpening, de-blurring, and edge enhancement. In this paper, various contrast enhancement filters used in license plate recognition are compared.
According to the overviews and analysis of adaptive brightness correction, we provide an available solution for the interference of environment light in digital cameras, but current methods are still not suitable for VLSI design. In this paper, we propose an efficient method, called local bi-histogram equalization (LBHE), to remedy the local visibility and control the degree of enhancement. We utilize...
This paper proposes a new contrast enhancement scheme which integrates a global and a local contrast enhancement schemes to reduce the blocking and the washed-out effects at the same time. The proposed method executes a block-based histogram equalization on the temporary images which are obtained by dividing an input image into sub-blocks so that the sub-block of each temporary image may have a block...
In this paper, we propose a new, fast image enhancement algorithm based on histogram equalization. The new algorithm uses full range of possible gray levels to specially enhance local interested areas, which has much improved the water-washed effect on enhanced CT head images caused by conventional histogram equalization algorithms. Compared with other histogram equalization based image enhancement...
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