Image and video processing techniques are widely employed in many fields, such as television broadcasting, video surveillance, medical imaging, industrial inspection and consumer electronics. With the rapid emergence of new display devices, large size video display units with high resolution and high frame rates are increasingly popular. But a corresponding improvement in video quality is still progressing slowly. Better video quality is always essential for either a better visual experience or more accurate image analysis. The key to better video quality is the development of specific video enhancement algorithms, and their hardware implementations. This paper proposes a group of systematic solutions, including both algorithms and hardware implementations, which solve three main problems in the video processing pipeline: (1) aliasing suppression in video scaling, (2) sharpness enhancement, and (3) exposure control and white balance. Aliasing is always introduced when scaling a video signal, bringing artifacts to the image, such as jagged edges. This paper analyzes the cause of aliasing and proposes a flexible video scaling algorithm framework. The proposed algorithm employs the sum of a B-spline kernel and its two high-order derivatives with different weights which can be adaptively changed for different applications to suppress aliasing. Many schemes from signal processing, hardware architecture, graph theory and so on, are employed to implement the hardware architecture of an arbitrary video scaling processor. The filters and scaling factors can be adjusted in both vertical and horizontal directions through simple register configuration during runtime. The processor qualifies as a high-performance, low-cost, reconfigurable hardware system. The sharpness of a video signal can be degraded by bandwidth constraints during acquisition and transmission, so improving the sharpness of video signals is of great importance, especially around the edges of an image. This paper proposes a video luminance and chrominance transient improvement algorithm to improve the sharpness of video signals, which utilizes the local features of an image and the difference of two Gaussian filters to enhance edges and smooth background. Meanwhile, the hardware architecture and FPGA based implementation of the algorithm is also presented. The system features favorable reconfigurability and reusability with a balance between performance and resource usage, and can be used as a ref...
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