Image Resolution Enhancing Techniques
Bi-Linear, Bi-Cubic and Adaptive SubPixel Interpolation Methods
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In this book, an image resolution enhancing technique for 2D images extracted from an integral 3D image is described. To improve the resolution of the view-point image, its size is increased in horizontal direction by using one of the following interpolation methods: Bilinear, Bicubic and adaptive sub pixel interpolation methods. In Bilinear method new pixel value is calculated by the weighted average of 2x2 neighborhood pixels. In Bicubic method new pixel value is computed by taking a weighted average of 4x4 nearest neighborhood pixels. In adaptive sub pixel interpolation method fourth and fi...
In this book, an image resolution enhancing technique for 2D images extracted from an integral 3D image is described. To improve the resolution of the view-point image, its size is increased in horizontal direction by using one of the following interpolation methods: Bilinear, Bicubic and adaptive sub pixel interpolation methods. In Bilinear method new pixel value is calculated by the weighted average of 2x2 neighborhood pixels. In Bicubic method new pixel value is computed by taking a weighted average of 4x4 nearest neighborhood pixels. In adaptive sub pixel interpolation method fourth and fifth columns behind the micro lenses are extracted to obtain the fourth and fifth view point images. 1) Dimensional characteristics curves are extracted for both the frames. Vertical displacement value is calculated by aligning one curve with other Low resolution frame is incremented with vertical displacement value, which is known as aligned frame i.e. fifth pixel sub image. Then the interpolation process is performed using aligned frame and previous frame i.e. fourth pixel frame. Thus the high resolution image is obtained from several low resolution image frames.
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