25-08-2017, 09:32 PM
FPGA IMPLEMENTATION OF CONTRAST ENHANCEMENT IN IMAGES USING XILINX SYSTEM GENERATOR
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Abstract
Enhancement for the digital images is
applicable in multiple domains. This paper presents
about the implementation of image contrast
enhancement using Xilinx System Generator (XSG).
The algorithm that is used to enhance the images is
CLAHE. The design is implemented in Spartan3E-
starter kit and Spartan6-LX9-microboard and the
results were compared. In spite of using minimum
resources the XGS based implementation preserves the
quality of the image.
INTRODUCTION
The employment of digital images has
become a subject of widespread interest in different
areas such as medical, outer space exploration and
many others. The main objective of image
processing is to improve the quality of the images
for human interpretation, or the perception of the
machines independently. This paper focuses on
processing an image pixel by pixel.
The degradation of an image may be
caused by many reasons like non-configured image
acquisition device or by unsuitable climatic
conditions. The ultimate aim of the paper is to
provide an effective method for enhancing such
degraded images using a hardware background. For
similar specification, image degradation as such as
by poor lighting [Fig 5a], fog [Fig 5b], low contrast
[Fig 5c] with obscured detail are considered and
processed.
POINT PROCESSING
The digital image acquired is sampled and
mapped as picture elements (pixels). The images
are treated as 2D matrices. Hence, all the
operations that can be applied to matrices would be
applicable to the images as well.
Point processes are the simplest and basic
image processing operations. They operate on a
pixel bases solely on that pixel’s value. Although
point operations are the simplest, they contain some
of the most powerful and widely used of all image
processing operations. They are especially useful in
image pre-processing, where an image is required
to be modified before the main processing is
attempted.
CONCLUSION
The FPGA implementation of contrast
enhancement for images with poor lighting, low
contrast, fogged are discussed. The resource
utilized by different image enhancements for
SPARTAN 3E as well as SPARTAN 6LX9 are
tabulated. From the tabulated results it is evident
that the employment of XSG for image contrast
enhancemnet consumes fewer resources [TABLE
III].