Edge enhancement

About: Edge enhancement is a research topic. Over the lifetime, 2324 publications have been published within this topic receiving 30962 citations.

Transform domain measure of enhancement — TDME — For security imaging applications

Abstract: Today, many security applications rely on imaging sensors. However, the quality of the captured image is highly susceptible to environmental lighting conditions such as poor or non-uniform illumination. Security imaging systems rely on efficient real-time image enhancement. For autonomous systems, determining and producing the best visually enhanced image output as perceived by the human visual system remains a challenge. In this paper, we present a metric for autonomous evaluation that will enable security systems to automatically determine the best human visual quality image. To achieve this, we have established a “no parameter no reference” metric that can determine the best visually pleasing image. The metric is algorithm independent such that it can be utilized for a diversity of enhancement algorithms. We present our DCT transform domain measure of enhancement (TDME). Unlike spatial domain measure of enhancement methods, the proposed measure is independent of image attributes and does not require any parameter selections to operate. The proposed measure is applicable to compressed and non-compressed images and can be used as an enhancement metric in conjunction with many different image enhancement methods.

Compact optical correlator: pre-processing and filter encoding strategies applied to images with varying illumination

Abstract: We present a portable, versatile optical pattern recognition system that can process 256x256 pixel images at high speed. The system is fully controlled by Windows-based software and can easily be switched between VanderLugt and joint transform operation. It combines the advantages of optics and electronics to form an advanced hybrid system where pre- and postprocessing algorithms can be varied depending on the application. Simulation and experimental results show that edge enhancement combined with binarization gives good results when applied to images where the illumination is varying.

Digital Boundary Detection Techniques For The Analysis Of Gated Cardiac Scintigrams

Abstract: Boundary detection in conventional nuclear medicine scintigrams is often difficult for several reasons. First, scintigrams generally have a low signal-to-noise ratio. Second, edge structures are poorly defined because of the low resolution of gamma ray cameras; and finally, edge contrast is usually reduced by foreground and background activity. In this paper we report on heuristic approaches we have taken to solve these problems and to develop programs for the display of cardiac wall motion and for the automatic determination of left ventricular ejection fraction. Our approach to processing cardiac scintigrams entails several steps: smoothing, edge enhancement, and contour extraction. We discuss each of these steps in light of the goal of producing cardiac boundaries which are spatially and temporally smooth and continuous. Boundary detection results are presented for some selected clinical images.