Abstract. Potential methods and facilities of registration of radiation is
growing. There are specific requirements for the detectors of optical
radiation: high sensitivity and resolution. The most complex biological receiver of optical radiation is the
human eye. Many ophthalmologists believe that a healthy eye is in constant
motion, as if feeling the object of consideration. This leads to increasing of spatial
resolution. Due to eye movements it is possible to form a dynamic image
containing the spatial increment of the luminance and chrominance stare at the
object. This dynamic image is an analogue of the derivative which is computed
along a trajectory equivalent to the trajectory of the eyes motion. The latest research and development in the
field of digital detectors of optical radiation show that one of the urgent
tasks is to increase the spatial resolution. At the same time, increasing of spatial
resolution by decreasing the linear dimensions of the pixels of the image
sensor is complicated by the fact that reducing the size of the useful area of
the pixel decreases the sensitivity of the matrices and, respectively, of the
useful signal-to-noise ratio. Thus, the problem of improving of spatial
resolution while preserving the linear size of the pixels is actual. It is proposed to increase the resolution
of optical receivers due to the formation of a sequence of shifted frames and their
further conversion. The goal of the transformation is the image recovery of high
resolution (super-resolution).
The article discusses the ways
to achieve super-resolution image sensors due to the formation and subsequent
processing of a sequence of shifted images. The article contains: the
mathematical apparatus of realization, methods and tools for physical
implementation, the simulation of the proposed method in MATLAB, given a
program listing and an example of the results of the program.
Finally, it contains conclusions
and references.
Keywords:
superresolution, image sensor, single-pixel camera, deconvolution,
digital signal processing.
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