Pixel Threshold Adjustment for Enhancing Degraded Frames of Uncompressed AVI

High noise level from darkness and low dynamic range severely degrade the visual quality of image or video. From previous few years there has been vital work on video process and improvements in Digital cameras. Still there is a problem in modern digital cameras to capture high dynamic range images and videos in low-light conditions. To resolve such issues associated with the deficient quality of low light there exist video enhancement technique which is used to make object standout from their background and become more detectable. Effective framework approach for Low vision frames enhancement using pixel threshold adjustment for enhancing degraded frames of uncompressed AVI has been proposed; aim to get clear video from low light or dark environments

ROBOMIRROR: A SIMULATED MIRROR DISPLAY WITH A ROBOTIC CAMERA

Simulated mirror displays have a promising prospect in applications, due to its capability for virtual visualization. In most existing mirror displays, cameras are placed on top of the displays and unable to capture the person in front of the display at the highest possible resolution. The lack of a direct frontal capture of the subject\u27s face and the geometric error introduced by image warping techniques make realistic mirror image rendering a challenging problem. The objective of this thesis is to explore the use of a robotic camera in tracking the face of the subject in front of the display to obtain a high-quality image capture. Our system uses a Bislide system to control a camera for face capture, while using a separate color-depth camera for accurate face tracking. We construct an optical device in which a one-way mirror is used so that the robotic camera behind can capture the subject while the rendered images can be displayed by reflecting off the mirror from an overhead projector. A key challenge of the proposed system is the reduction of light due to the one-way mirror. The optimal 2D Wiener filter is selected to enhance the low contrast images captured by the camera

SAFE: a Self Adaptive Frame Enhancer FPGA-based IP-core for real-time space applications

Video-based navigation is an increasingly used procedure with hard real-time requirements and high computational effort. In this field, FPGA hardware accelleration supplyes low-cost and considerable performances enhancement. The video-based navigation algorithms extrapolate and correlates features from images, relying on their accuracy. Image enhancement provides more defined and contrasted frames, assuring high precision feature extraction. This work introduces an FPGA-based self-adaptive image enhancer. The IP-core is suitable for hard-real time applications, such as space applications, thanks to the guaranteed high-throughpu