Binary Tree-based Generic Demosaicking Algorithm for Multispectral Filter Arrays
| Autor: | Rajeev Ramanath, Wesley E. Snyder, Hairong Qi, Lidan Miao |
|---|---|
| Rok vydání: | 2006 |
| Předmět: |
Demosaicing
Contextual image classification Color image business.industry Multispectral image Color Information Storage and Retrieval Image processing Image segmentation Image Enhancement Computer Graphics and Computer-Aided Design Image Interpretation Computer-Assisted Colorimetry Computer vision Color filter array Artificial intelligence business Image resolution Algorithm Algorithms Filtration Software Mathematics |
| Zdroj: | IEEE Transactions on Image Processing. 15:3550-3558 |
| ISSN: | 1057-7149 |
| DOI: | 10.1109/tip.2006.877476 |
| Popis: | In this paper, we extend the idea of using mosaicked color filter array (CFA) in color imaging, which has been widely adopted in the digital color camera industry, to the use of multispectral filter array (MSFA) in multispectral imaging. The filter array technique can help reduce the cost, achieve exact registration, and improve the robustness of the imaging system. However, the extension from CFA to MSFA is not straightforward. First, most CFAs only deal with a few bands (3 or 4) within the narrow visual spectral region, while the design of MSFA needs to handle the arrangement of multiple bands (more than 3) across a much wider spectral range. Second, most existing CFA demosaicking algorithms assume the fixed Bayer CFA and are confined to properties only existed in the color domain. Therefore, they cannot be directly applied to multispectral demosaicking. The main challenges faced in multispectral demosaicking is how to design a generic algorithm that can handle the more diversified MSFA patterns, and how to improve performance with a coarser spatial resolution and a less degree of spectral correlation. In this paper, we present a binary tree based generic demosaicking method. Two metrics are used to evaluate the generic algorithm, including the root mean-square error (RMSE) for reconstruction performance and the classification accuracy for target discrimination performance. Experimental results show that the demosaicked images present low RMSE (less than 7) and comparable classification performance as original images. These results support that MSFA technique can be applied to multispectral imaging with unique advantages. |
| Databáze: | OpenAIRE |
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