Design And Analysis Of Algorithms For Obtaining Super Resolution Essay

Design And Analysis Of Algorithms For Obtaining Super Resolution Satellite Images - Essay Example The paper tells that the launching of satellites nowadays, experience transformations due to the increasing need for High Resolution images. History shows that once satellites are launched, updating of its captured images faces a challenge due to resolution problems. Some algorithms have been developed, which assist in transforming Low Resolution images to High Resolution images. High Resolution (HR) images have a wide range of usage in the various fields, for example, medical imaging, video surveillance, and satellite imaging. However, due to limitations of hardware, many Low Resolution (LR) images are obtained than High Resolution images. As a result, researchers have come up with new techniques that help them in obtaining HR images from LR images. Researchers have come up with a reconstruction technique known as Super-resolution (SR) technique. The technique solves the problem of developing HR images from LR images since it allows the recovery of high resolution images from low re solution images. The technique allows recovery of HR images from several LR images, which are blurred, noisy and down-sampled. The SR technique uses some algorithms in order to solve the resolution problem. These algorithms use LR images that are related to each other’s through random translations and rotations in order to create a single HR image of the original scene. In order to reconstruct the HR image, the LR images must be first registered relative to a specific frame of reference. Secondly, the pixels from the LR images are used to sparsely populate some of the pixels of the high resolution image. ... This may include the implementation of set of super resolution algorithms and comparing their performances. Although there is the quest of obtaining high resolution images, there are some challenges that go hand in hand with the high resolution. In acquiring high resolution imaging systems, one runs into the problem of diminishing returns. The optical components and imaging chips necessary for high resolution imaging are very expensive since they cost millions of dollars. Potential Benefits High image resolution is beneficial since there is an increase in image detail. In addition, image resolution results in images that do not contain noise or with reduced noise and images with increased smoothness in interlaced video. Chapter Two Fundamentals of Image Processing Introduction and definition Image processing refers to any kind of signal processing, where the input is an image, for instance, a video frame or a photograph and the resulting output of the image may be either an image or a set of parameters or characteristics that are related to the image. In most image processing techniques, the image is treated as a two-dimensional signal. The image processing techniques usually apply standard signal processing techniques to the image being processed. During image processing, various operations may be carried out on the image; such operations include Euclidean geometrical transformations that may take the form of reduction, rotation and enlargement, color corrections that may involve color balancing, color mapping, quantization and contrast adjustment (Burge & Burge, 2009). Image processing operations may also include interpolation, image registration, and image segmentation.