Image enhancement technology research for army applications

Abstract

Recognition and identification ranges are limited to the quality of the images. Both the received contrast and the spatial resolution determine if objects are recognizable. Several aspects affect the image quality. First of all the sensor itself. The image quality depends on the size of the infrared detector array and the sensitivity. Second, also the intervening atmosphere, in particular over longer ranges, has an impact on the image quality. It degrades the contrast, due to transmission effects, as well as it influences the resolution, due to turbulence blur, of the image. We present studies in the field of infrared image enhancement. Several techniques are described: noise reduction, super resolution, turbulence compensation, contrast enhancement, stabilization. These techniques operate in real-time on COTS/MOTS platforms. They are especially effective in the army theatre, where long horizontal paths, and short line-of-sight limited urban operations are both present. Application of these techniques on observation masts, such as on military camp sites, and on UAVs and moving ground vehicles are discussed. Examples will be presented from several trials in which these techniques were demonstrated, including the presentation of test results.

Computed Tomography Image Enhancement Using Cuckoo Search: A Log Transform Based Approach

“…Image enhancement is one of the protruding research areas in image processing as it is more favorable in numerous applications, namely: military [1], satellite image processing [2], geographical imaging [3] and medical image processing [4]. Its techniques are used to process a given image to recognize its features easily [5] clarifying its details that cannot be immediately observed in the original image, especially when the image is corrupted with high level of speckle noise [6] or has insufficient contrast [7] [8].…”

Turbulence mitigation methods for sea scenario imaging

“…Existing processing algorithms for such data sets are based on the assumption of a static background. Indeed, our standard method provides good results for several land 1 and harbor 2 scenes, but this approach cannot be used for sea scenarios for two main reasons: the non-static background, and targets that have complex movements. At sea, turbulence can therefore affect the classification and identification of ships (e.g., for security and defense purposes).…”

Image processing provides better views under water

“…Further details on image registration for enhancement purposes are available elsewhere. 1 Underwater imagery may also suffer from low contrast, especially in murky waters and when observing over larger distances. Amplifying the small contrast variations achieves a higher, evenly divided contrast for the entire image.…”

“…Here, we describe a software solution for enhancing underwater imagery. Wherever possible, we have reused algorithms based on earlier developments in the area of compound security 1 and UAV (unmanned aerial vehicle) image 2 enhancement, and have transformed and extended them for this underwater case. Our method comprises three techniques.…”