A FAST AND ROBUST FRAMEWORK FOR IMAGE FUSION AND ...

List of Figures
1.1 A block diagram representation of image formation and multi-frame image reconstruction
in a typical digital imaging system. The forward model is a mathematical
description of the image degradation process. The inverse problem
addresses the issue of retrieving (or estimating) the original scene from the lowquality
captured images. . . ........................... 2
1.2 An illustrative example of the motion-based super-resolution problem. (a) A
high-resolution image consisting of four pixels. (b)-(e) Low-resolution images
consisting of only one pixel, each captured by subpixel motion of an imaginary
camera. Assuming that the camera point spread function is known, and the
graylevel of all bordering pixels is zero, the pixel values of the high-resolution
image can be precisely estimated from the low-resolution images. . . . .... 3
1.3 Super-resolution experiment on real world data. A set of 26 low quality images
were fused resulting in a higher quality image. One captured image is shown in
(a). The red square section of (a) is zoomed in (b). Super-resolved image in (c)
is the high quality output image. ......................... 5
2.1 Block diagram representation of (2.1), where X(x, y) is the continuous intensity
distribution of the scene, V is the additive noise, and Y is the resulting
discrete low-quality image. . ........................... 12
2.2 Simulation results of outlier effects on super-resolved images. The original
high-resolution image of Lena in (a) was warped with translational motion and
down-sampled resulting in four images such as (b). (c) is an image acquired
with downsampling and zoom (affine motion). (d) Reconstruction of these four
low-resolution images with least-squares approach. (e) One of four LR images
acquired by adding salt and pepper noise to set of images in (b). (f) Reconstruction
of images in (e) with least-squares approach. ................ 19
vi