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Vol. 193, Issue 10, October 2015, pp. 50-56




Superpixel Compressive Sensing Recovery of Spectral Images Sensed by Multi-patterned
Focal Plane Array Detectors

1 Yuri H. MEJIA, 2 Fernando A. ROJAS, 2 Henry ARGUELLO

1 Department of Electrical Engineering, Universidad Industrial de Santander, Colombia
2 Department of Systems Engineering and Computer Science, Universidad Industrial de Santander, Colombia
Tel.: +57 7 6344000

E-mail: yuri.mejia@correo.uis.edu.co, frojas@uis.edu.co, henarfu@uis.edu.co


Received: 31 August 2015 /Accepted: 5 October 2015 /Published: 30 October 2015

Digital Sensors and Sensor Sysstems


Abstract: Conventional spectral imaging systems capture spectral and spatial information from a scene to produce a spectral data cube by scanning procedures. Photolithography technology development enables the production of complex filters by combining patterning techniques with optical coatings. These filters can be directly deposited onto detector arrays in order to measure spectral information with a unique snapshot. Nevertheless, recovering the spectral image with traditional methods following a demosaicing approach is impractical. State-of-the-art establishes multispectral demosaicing for recovering images with a specific spatio-spectral resolution depending on the number of pixels in the detector and the filter mosaic. Recently compressive sensing technique has been developed that allows recovering signals with few measurements than the traditional methods by using the sparse representation of the underlying signal. The selection of superpixels in the multi-patterned focal plane array detectors to calculate the spectral response of a single pixel in the reconstructed spectral images could improve the reconstruction, based on exploiting the sparse representation of the spectral images. This paper presents a model for spectral images recovering from superpixels formed with multi-patterned focal plane array detectors measurements using the concept of compressive sensing. This model selects subsets of the superpixels measurements following a downsampling matrix operation, therefore a reconstruction model is formulated by directly reconstruct a spectral image with the spectral resolution given by the number of filters. The superpixel size selection leads to a variable recovered spatial resolution preserving the filters spectral resolution. Multi-patterned focal plane array detectors measurements for real spectral images are simulated in order to verify the effectiveness of the recovery model. An ensemble of random dichroic and band pass filters is used. The superpixel compressive sensing reconstruction approach and the demosaicing scheme reconstruction are compared.


Keywords: Compressive sensing, Spectral images, Multi-patterned focal plane array detectors, Superpixel.


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