Application Of Image Enhancement Techniques Research Articles

MedGA: A novel evolutionary method for image enhancement in medical imaging systems

Medical imaging systems often require the application of image enhancement techniques to help physicians in anomaly/abnormality detection and diagnosis, as well as to improve the quality of images that undergo automated image processing. In this work we introduce MedGA, a novel image enhancement method based on Genetic Algorithms that is able to improve the appearance and the visual quality of images characterized by a bimodal gray level intensity histogram, by strengthening their two underlying sub-distributions. MedGA can be exploited as a pre-processing step for the enhancement of images with a nearly bimodal histogram distribution, to improve the results achieved by downstream image processing techniques. As a case study, we use MedGA as a clinical expert system for contrast-enhanced Magnetic Resonance image analysis, considering Magnetic Resonance guided Focused Ultrasound Surgery for uterine fibroids. The performances of MedGA are quantitatively evaluated by means of various image enhancement metrics, and compared against the conventional state-of-the-art image enhancement techniques, namely, histogram equalization, bi-histogram equalization, encoding and decoding Gamma transformations, and sigmoid transformations. We show that MedGA considerably outperforms the other approaches in terms of signal and perceived image quality, while preserving the input mean brightness. MedGA may have a significant impact in real healthcare environments, representing an intelligent solution for Clinical Decision Support Systems in radiology practice for image enhancement, to visually assist physicians during their interactive decision-making tasks, as well as for the improvement of downstream automated processing pipelines in clinically useful measurements.

The limit values for brightness and contrast adjustment in digital panoramic radiography

There is an overall lack of studies about digital panoramic radiography. The application of image enhancement techniques is still being done based on the operator’s preferences, since there is no objective limitation. The aim is to evaluate the limit values of the brightness and contrast adjustment in digital panoramic radiography. Digital panoramic radiographs were divided into three groups (dark, medium, and light), and the contrast and brightness adjustments were done using Digora for Windows. The static evaluations were done using three criteria: 1 if the image had lower quality, 2 if there was no difference and 3 if the image had better quality. The radiographic changes differed in each group depending on the initial imaging conditions. The brightness adjustment limit values in the dark and medium groups were −10 and +20, respectively, and −20 and +10 in the light group. The contrast adjustment limit values in all of the groups were −10 and +10.

WorldView2 satellite imagery in remote sensing a past gold trading trail in Luzon: Testing ethnohistory-based and GIS-based models

This article examines the application of image enhancement techniques on high resolution and multi-spectral WorldView 2 satellite images in aid of remote sensing a past gold trading trail in Northwestern Luzon that was used from the PreSpanish Contact Period 10th to 16th c and the Spanish Contact Period (17th to 19th c). In delineating the corridor for the research, several ethnohistorical accounts were followed as interlocutors. The article posits that segments of the Aringay-Tonglo-Balatok gold trail are still visible on the landscape while other segments may have been converted to contemporary farm-to-market roads. Identification of the segments was made possible by application of image enhancement techniques on WorldView2 satellite imagery including resolution merge using Brovey transform, unsupervised classification using a fusion of built-up index and vegetation index. Satellite band combination for mining operations (yellow-NIR1-red edge), modified false color Infrared (NIR1-green-blue), and soils and constructions (red-blue-yellow) have also been of immense utility.

UNDERWATER 3D MODELING: IMAGE ENHANCEMENT AND POINT CLOUD FILTERING

Abstract. This paper examines the results of image enhancement and point cloud filtering on the visual and geometric quality of 3D models for the representation of underwater features. Specifically it evaluates the combination of effects from the manual editing of images’ radiometry (captured at shallow depths) and the selection of parameters for point cloud definition and mesh building (processed in 3D modeling software). Such datasets, are usually collected by divers, handled by scientists and used for geovisualization purposes. In the presented study, have been created 3D models from three sets of images (seafloor, part of a wreck and a small boat's wreck) captured at three different depths (3.5m, 10m and 14m respectively). Four models have been created from the first dataset (seafloor) in order to evaluate the results from the application of image enhancement techniques and point cloud filtering. The main process for this preliminary study included a) the definition of parameters for the point cloud filtering and the creation of a reference model, b) the radiometric editing of images, followed by the creation of three improved models and c) the assessment of results by comparing the visual and the geometric quality of improved models versus the reference one. Finally, the selected technique is tested on two other data sets in order to examine its appropriateness for different depths (at 10m and 14m) and different objects (part of a wreck and a small boat's wreck) in the context of an ongoing research in the Laboratory of Photogrammetry and Remote Sensing.

UNDERWATER 3D MODELING: IMAGE ENHANCEMENT AND POINT CLOUD FILTERING

This paper examines the results of image enhancement and point cloud filtering on the visual and geometric quality of 3D models for the representation of underwater features. Specifically it evaluates the combination of effects from the manual editing of images’ radiometry (captured at shallow depths) and the selection of parameters for point cloud definition and mesh building (processed in 3D modeling software). Such datasets, are usually collected by divers, handled by scientists and used for geovisualization purposes. In the presented study, have been created 3D models from three sets of images (seafloor, part of a wreck and a small boat's wreck) captured at three different depths (3.5m, 10m and 14m respectively). Four models have been created from the first dataset (seafloor) in order to evaluate the results from the application of image enhancement techniques and point cloud filtering. The main process for this preliminary study included a) the definition of parameters for the point cloud filtering and the creation of a reference model, b) the radiometric editing of images, followed by the creation of three improved models and c) the assessment of results by comparing the visual and the geometric quality of improved models versus the reference one. Finally, the selected technique is tested on two other data sets in order to examine its appropriateness for different depths (at 10m and 14m) and different objects (part of a wreck and a small boat's wreck) in the context of an ongoing research in the Laboratory of Photogrammetry and Remote Sensing.

Application of Image Enhancement Technology in Bubble Dimension Measurement of Deinked Pulp Flotation Column

A substantial increase in demand of paper causes a severe shortage of wood, paper recycling have become increasingly important; Deinked pulp flotation column has the features of less site area, good treatment efficiency, easily control and so on, which can be wildly used in fiber recycling in abroad. This thesis uses the working principle of ore dressing to recycle secondary fiber in order to apply flotation column in wastepaper recycling. And meanwhile this article primarily study on deinked pulp flotation column which is imported from Canada, and drawing 2D maps of flotation column, Meanwhile comparing the application of image enhancement techniques in bubble dimension measurement of deinked pulp flotation column.

Query quality refinement in singular value decomposition to improve genetic algorithms for multimedia data retrieval

With the development of internet and availability of multimedia data capturing devices, the size of Multimedia Digital Database (MDD) collection is increasing rapidly. The complex data presented by such systems do not have the total ordering property presented by the traditional data handled by Database Management Systems (DBMSs). The quality of the search experience in such systems is also normally a big challenge since users from various domains require efficient data searching, browsing and retrieval tools. This has triggered an important research topic in Multimedia information retrieval concerning efficient and effective image similarity search. Modern search algorithms are fast and effective on a wide range of problems, but on MDD with a large number of parameters and observations, manipulations of large matrices, storage and retrieval of large amounts of information may render an otherwise useful method slow or inoperable. The focus of this work is the application of image enhancement technique, using histogram equalization, to the images retrieved using singular value decomposition (SVD). SVD is a linear algebra technique used for discovering correlations within data. The approach, herein referred to as query quality refinement (QQR) technique, improves the image similarity search result, and when incorporated with genetic algorithms further optimizes the search. These beneficial applications can be extended to other different types of multimedia data in various areas such as the P2P and WiMAX networks.

Application of image enhancement techniques to potential field data

In this paper the application of image enhancement techniques to potential field data is briefly described and two improved enhancement methods are introduced. One method is derived from the histogram equalization technique and automatically determines the color spectra of geo- physical maps. Colors can be properly distributed and visual effects and resolution can be enhanced by the method. The other method is based on the modified Radon transform and gradient calculation and is used to detect and enhance linear features in gravity and magnetic images. The method facilites the detection of line segments in the transform domain. Tests with synthetic images and real data show the methods to be effective in feature enhancement.

Fingerprint Identification Using Image Enhancement Techniques

Abstract This report presents an application of image enhancement techniques in fingerprints as a tool for forensic sciences. Digital image processing technology was applied to restore fingerprints with non-uniform contrast. Whenever the results obtained by applying conventional enhancement techniques were not satisfactory, we combined spatial domain as well as frequency domain techniques in order to enhance the features that allowed later identification. The fingerprints correspond to a person who was murdered by military forces in 1976. The processed fingerprints where sent to the Court of Justice where forensic experts could finally find out the identity of a person who had been unknown until that moment.

Application of image enhancement techniques to magnetic resonance imaging.

Image enhancement techniques are widely available, but their applications are not well defined. The authors encourage radiologists to become familiar with these techniques, to evaluate them, and to incorporate them into specific display protocols.

Value of image enhancement and injection of contrast medium for right ventricular volume determination by two-dimensional echocardiography in congenital heart disease

To determine factors that influence the accuracy of echocardiographically estimated right ventricular volume and to improve the echocardiographic input information by applying image enhancement techniques, quantitative contrast echocardiography (4-chamber view) and biplane angiocardiography were performed in 23 children during routine diagnostic cardiac catheterization. Volumes calculated on the basis of unprocessed and processed echocardiographic cross sections (area-length method and sphere model) underestimated angiocardiographic volumes significantly (p < 0.01), and more so in end-diastole (50.6%) than in end-systole (35.9%). Thus, ejection fraction was significantly (p < 0.01) underestimated; mean values were 0.48 ± 0.12 and 0.60 ± 0.08, respectively. The best comparison between echocardiography and angiocardiography at end-diastole was achieved with the sphere model using image enhancement techniques and injection of contrast media, where y = 0.54x − 6.8, r = 0.97, sy.x = 7.3. Correlations, however, in which unprocessed echocardiograms were used showed only slightly less good correlations. With the 6 image-enhancement techniques, a more homogeneous structure of the image and a more distinct outline of the internal surface was achieved. The statistical error improved only slightly. The echocardiographic 4-chamber view allows right ventricular volume determination with an acceptable accuracy. Its underestimation is related to inadequate visualization of trabeculations and mainly to the models used. Application of image enhancement techniques allows easier outlining of the internal cavity surface. The advantage gained by the combination of contrast injection and image enhancement techniques does not warrant the routine central injection of available contrast material.