1. A method comprising: capturing a first plurality of low resolution images and a second plurality of low resolution images through a corresponding first sensor and a second sensor, the first sensor having a higher resolution than the second sensor; estimating, through a processor, expansion coefficients of polyphase components of an enhanced resolution image based on the second plurality of low resolution images, the expansion coefficients being expressed in terms of the first plurality of low resolution images, and the polyphase components of the enhanced resolution image being shifted and downsampled versions thereof, wherein estimating, through the processor, the expansion coefficients of the polyphase components of the enhanced resolution image includes: selecting a low resolution image of the second plurality of low resolution images as a reference polyphase component of the enhanced resolution image to be determined, the reference polyphase component being a shifted and a J×J downsampled version of the enhanced resolution image, wherein selecting the reference polyphase component of the enhanced resolution image includes: avoiding low resolution images from the second plurality of low resolution images that are farthest from a downsized mean of the first plurality of low resolution images; selecting the low resolution image having high frequency components larger than another low resolution image in the second plurality of low resolution images as the reference polyphase component; estimating a sub-polyphase component of each of a plurality of primary polyphase components of the enhanced resolution image, the primary polyphase components being shifted and I×I downsampled versions of the enhanced resolution image, I and J being integers, J>I>1, and the sub-polyphase component being a shifted and an J×J downsampled version of the corresponding each of the plurality of primary polyphase components of the enhanced resolution image; estimating expansion coefficients of the each of the plurality of the primary polyphase components of the enhanced resolution image based on the estimated sub-polyphase component thereof to determine the enhanced resolution image, the expansion coefficients enabling the each of the plurality of the primary polyphase components to be expressed as a linear combination of the first plurality of low resolution images, wherein a resolution of the enhanced resolution image is I times that of the first sensor and J times that of the second sensor, wherein the sub-polyphase component of the each of the plurality of primary polyphase components of the enhanced resolution image is also a sub-polyphase component of the reference polyphase component of the enhanced resolution image corresponding to a shifted and a I×I downsampled version thereof; estimating the enhanced resolution image a plurality of times based on the selected reference polyphase component, the plurality of times ranging between 2 and J 2 ; determining a final version of the enhanced resolution image based on a smoothness thereof: denoising, through the processor, the first plurality of low resolution images and the second plurality of low resolution images prior to estimating the sub-polyphase component of the each of the plurality of primary polyphase components and the expansion coefficients thereof; denoising, through the processor, the final version of the enhanced resolution image to enhance a quality thereof, wherein denoising the first plurality of low resolution images and the second plurality of low resolution images includes: downsampling the first plurality of low resolution images and the second plurality of low resolution images by J×J and I×I respectively; estimating a mean and a covariance of sub-low resolution images obtained through the downsampling; denoising the first plurality of low resolution images and the second plurality of low resolution images through Principal Component Analysis (PCA) based on the estimated covariance; wherein denoising the final version of the enhanced resolution image to enhance the quality thereof is based on Total Variation (TV) denoising; sharpening the final version of the enhanced resolution image through Unsharp Masking (UM); and removing irregularities in pixel intensity levels through a median filter.