© 2014, IJCSE All Rights Reserved 168
Review Paper Volume-2, Issue-5 E-ISSN: 2347-2693
A Comprehensive Review of Improvement of Image Contrast in Case of Poor Light
Pratiksha Mishra
1*
, Amit Sinhal
2
and Deepak Singh Tomar
3
1*,2,3
Dept of Computer Science & Engg, Technocrats Institute of Technology, Bhopal, Madhya Pradesh, India
www.ijcseonline.org
Received: 10/04/2014 Revised: 24 /04/2014 Accepted: 19/05/ 2014 Published: 31 /05/2014
Abstract: In this paper, we are reviewing several research papers regarding study and analysis towards improvement of image
contrast in case of poor light. In this paper we most focus on many algorithms that has been designed for enhancement of image,
At the end, a study has been made by comparing all the proposed parameters that with certain advantages and having limitations
too, that have been conducted a relevant experimental analysis to evaluate both their robustness and their performance. Our
review work involves a comparative study of Improvement of Image Contrast for image enrichment with respect to the following
parameter Performance, Scalability, Image enhancement, Image Acquisition, Applying Morphological operators, Detecting and
extracting the background, Applying contrast enhancement operators:- block analysis and opening by reconstruction, Applying
image enhancement techniques like image sharpening etc.
Keywords: Digital Image Processing, Denoiser, Morphological Operators, Filters, Image contrast, Image segmentation
I. INTRODUCTION
Digital Image process is that the use of laptop algorithms to
perform image process on Digital pictures. As a subfield of
digital signal process, digital image process has several
blessings over analog image process. It permits a way wider
vary of algorithms to be applied to the input file, and might
avoid issues like the build-up of noise and signal distortion
throughout process [1], [2]. Since pictures are outlined over
two dimensions (perhaps more) digital image process could
also be sculptural within the type of four-dimensional Systems.
Image improvement could be a helpful technique in image
process that allows the development of the visual look of the
image or provides a remodeled image that permits alternative
image process tasks (image segmentation, for
example).Methods in image improvement are usually classified
into spatial strategies and frequency domain ones. The
intensity i.e. the distinction between highest and lowest
intensity values in a picture offers a live of its distinction.
Contrast enhancement is an important task in image processing
that is commonly used as a preprocessing step to improve the
images for other tasks such as segmentation. However, some
methods for contrast improvement that work well in low-
contrast regions affect good contrast regions as well. This
occurs due to the fact that some elements may vanish. A
method focused on images with different luminance conditions
was also introduced.
Image process techniques were first developed in 1960 through
the collaboration of a good vary of scientists and teachers. The
most focus of their work was to develop medical imaging,
character recognition and build prime quality pictures at the
microscopic level. Throughout this era, instrumentality and
process prices were prohibitively high. The monetary
constraints had a heavy impact on the depth and breadth of
technology development that might be done. By the Nineteen
Seventies, computing instrumentality prices [3] had born
considerably creating digital image process a lot of realistic.
Film and software package firms endowed important funds
into the event and sweetening of image process, making a
brand new trade.
Image process is any variety of signal process that the input is
a picture, like a photograph or video frame; the output of
image process is also either a picture or, a collection of
characteristics or parameters associated with the image. Most
image-processing techniques involve treating the image as a
two-dimensional signal and applying commonplace signal-
processing techniques to that. Image process typically refers to
digital image process, however optical and analog image
process is also attainable. The acquisition of pictures
(producing the input image within the first place) is named as
imaging. Image process may be a physical method wont to
convert a picture signal into a physical image. The image
signals are often either digital or analog. The particular output
itself is often associate degree actual physical image or the
characteristics of a picture. The foremost common variety of
image process is photography.
The application of mathematical morphology to image process
and analysis has initiated a replacement approach for finding
variety of issues within the connected field. This approach
relies on set supposed ideas [4] of form. In morphology objects
gift in a picture square measure treated as sets. The
identification of objects and object options through their form
makes mathematical morphology become a noticeable
approach for varied machine vision and recognition processes.
Very often a recorded image suffers from a typical degradation
like poor distinction. The intensity i.e. the distinction between
the best and lowest intensity values [5] in a picture provides a
live of its distinction. The primary work handling distinction
Corresponding Author: Pratiksha Mishra