A High Resolution Color Image Restoration Algorithm for Thin TOMBO Imaging Systems

Amar A El-Sallam,Farid Boussaid

doi:10.3390/s90604649

Amar A El-Sallam, Farid Boussaid

Open Access

https://doi.org/10.3390/s90604649

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Journal: Sensors (Basel, Switzerland)	Publication Date: Jun 15, 2009
Citations: 6	License type: CC BY 3.0

Affiliation: University of Western Australia

Abstract

In this paper, we present a blind image restoration algorithm to reconstruct a high resolution (HR) color image from multiple, low resolution (LR), degraded and noisy images captured by thin (< 1mm) TOMBO imaging systems. The proposed algorithm is an extension of our grayscale algorithm reported in [1] to the case of color images. In this color extension, each Point Spread Function (PSF) of each captured image is assumed to be different from one color component to another and from one imaging unit to the other. For the task of image restoration, we use all spectral information in each captured image to restore each output pixel in the reconstructed HR image, i.e., we use the most efficient global category of point operations. First, the composite RGB color components of each captured image are extracted. A blind estimation technique is then applied to estimate the spectra of each color component and its associated blurring PSF. The estimation process is formed in a way that minimizes significantly the interchannel cross-correlations and additive noise. The estimated PSFs together with advanced interpolation techniques are then combined to compensate for blur and reconstruct a HR color image of the original scene. Finally, a histogram normalization process adjusts the balance between image color components, brightness and contrast. Simulated and experimental results reveal that the proposed algorithm is capable of restoring HR color images from degraded, LR and noisy observations even at low Signal-to-Noise Energy ratios (SNERs). The proposed algorithm uses FFT and only two fundamental image restoration constraints, making it suitable for silicon integration with the TOMBO imager.

Highlights

TOMBO (Thin Observation Module by Bound Optics) imaging systems are a new generation of paper-thin imaging products, which integrate micro-optics, photo-sensing elements and processingcircuitry all on one single silicon chip (Figure 1)
The paper is organized as follows: in section 2, we develop a model for a color TOMBO imager and derive the mathematical formulation of a novel blind color image restoration method
The proposed method will have the following characteristics: (i) it does not require prior information about the imaging system nor the original scene, and performs blind image restoration, (ii) it can remove blur and additive noise from the high resolution (HR) color image, (iii) it exploits all available information contained in the captured low resolution (LR) images, and (iv) it requires minimal computational complexity

Summary

Introduction

TOMBO (Thin Observation Module by Bound Optics) imaging systems are a new generation of paper-thin imaging products, which integrate micro-optics, photo-sensing elements and processingcircuitry all on one single silicon chip (Figure 1). The proposed spectral-based color image restoration method averages out all LR captured images, making the color channels globally independent of each other.

Results

Conclusion