Top 7 Image Enhancement Projects

Image enhancement is the course of action undertaken for enhancing the quality as well as the source data content prior to the actual processing of the image. For instance, slicing of density; FCC- False Colour Composite; spatial filtering; and improvement of contrast aspect, etc. are the generally adopted image enhancing processes adopted by the scholarly world.

This very technique will be able to empower any scientist or engineers to execute a bunch of process for acquiring the better quality and more clear image to well serve any application. MATLAB and OpenCV are the major tools that are mostly used for any image-related processing methodologies including the enhancement of image. In this write-up, we will discuss the top 7 image enhancement projects so that the students doing their projects in this genre could acquire, sharpen, and master every possible skillset. The curated top 7 image enhancement projects will be covering multiple applicational sectors like health care treatments, plant management, image engineering, etc.

The Top 7 Image Enhancement Projects to know for learning skills, sharpening the skills learned, and gaining expertise towards the project implementation:

1. Combining highlight removal and low-light image enhancement technique for HDR-like image generation 

As we are evolving in all the technological aspects, the genre of HDR- High Dynamic Range has gained immense attention in the arena of image processing sector.

Any image of the type LDR- Low Dynamic Range could be used for creating the Image of the type HDR with the true color strengthening and elimination of the specular component from the pixels in the highlight.

The successful conduct of any image enhancement-based projects lies on the acquisition and mastering a few important skillsets/ conceptions. Those are as follows: required level of knowledge in working with MATLAB; C language; C++ Language; Visual C++; Machine Learning; lighting techs; Remote sensing; Image processing fundamentals; Data investigation; and several skillsets required for any particular application, for instance, expertise with several imaging techniques like MRI- Magnetic Resonance Imaging, CT- Computed Tomography, etc. needed in case of image processing done from the context of healthcare sector.

2. Contrast Enhancement of Medical Images Using Statistical Methods with Image Processing Concepts 

The health care images often need to be clearly visible for right and precise clinical examination and diagnosis of any ailment to trigger required treatments and medications.

With the successful deployment of image processing conceptions as well as the statistical approaches, the unclear health care images could be made clear by appropriately enriching the image contrast.

The successful conduct of any image enhancement-based projects lies on the acquisition and mastering a few important skillsets/ conceptions. Those are as follows: required level of knowledge in working with MATLAB; Image fundamentals; C language; C++ Language; Visual C++; Machine Learning; Statistical methods; Remote sensing; health care systems; Image processing fundamentals; Data investigation; and several skillsets required for any particular application, for instance, expertise with several imaging techniques like MRI- Magnetic Resonance Imaging, CT- Computed Tomography, etc. needed in case of image processing done from the context of healthcare sector.

3. Color Correction Based on CFA and Enhancement Based on Retinex with Dense Pixels for Underwater Images 

The images captured or videos recorded in the deep-water condition could often cause the image to lack the color when compared to the color of any entity originally existing. 

The image under deep water conditions could be effectively corrected for its color and subsequently be enhanced by deploying the prospects of the CFA- Color Filter Array, dense pixels containing Retinex model.

The successful conduct of any image enhancement-based projects lies on the acquisition and mastering a few important skillsets/ conceptions. Those are as follows: required level of knowledge in working with MATLAB; C language; C++ Language; water properties affecting image; color correction approaches; Visual C++; Machine Learning; Remote sensing; Image processing fundamentals; Knowledge of pixels; Data investigation; and several skillsets required for any particular application, for instance, expertise with several imaging techniques like MRI- Magnetic Resonance Imaging, CT- Computed Tomography, etc. needed in case of image processing done from the context of healthcare sector.

4. Feature Detection and Matching with Lineous Adjustment and Adaptive Thresholding 

As far as the computer vision approaches are concerned, the detection of image specific attributes as well as the matching techs have viewed as the crucial constituents.

The issues realized in both the detection of image specific attributes as well as the matching techs could be easily redressed with the adaptive thresholding and lineous reconciliation.

The successful conduct of any image enhancement-based projects lies on the acquisition and mastering a few important skillsets/ conceptions. Those are as follows: required level of knowledge in working with MATLAB; C language; C++ Language; Visual C++; Machine Learning; Matching methods; Remote sensing; Image processing fundamentals; Data investigation; Feature identification; and several skillsets required for any particular application, for instance, expertise with several imaging techniques like MRI- Magnetic Resonance Imaging, CT- Computed Tomography, etc. needed in case of image processing done from the context of healthcare sector.

5. Image Quality Enhancement for Wheat Rust Diseased Images Using Histogram Equalization Technique 

In case of the floral disease identification, the images given as the input need to be clearer so as to ensure the correction diagnosis and timely treatment of the ailments. 

By successful deployment of the approach of Histogram Equalization, the rust diseases occurring in the wheat plants could be easily acted upon by due enhancement of the image quality for diagnosis purposes.

The successful conduct of any image enhancement-based projects lies on the acquisition and mastering a few important skillsets/ conceptions. Those are as follows: required level of knowledge in working with MATLAB; C language; C++ Language; Visual C++; Machine Learning; Remote sensing; diseases in plants; Image processing fundamentals; Data investigation; and several skillsets required for any particular application, for instance, expertise with several imaging techniques like MRI- Magnetic Resonance Imaging, CT- Computed Tomography, etc. needed in case of image processing done from the context of healthcare sector.

6. Nighttime Image Enhancement Using a New Illumination Boost Algorithm 

The images captured or videos recorded in the reduced lighting condition could often cause the image to lack contrast and brightness. Furthermore, those images might be containing latent colors in it. 

The night time captured image specific aspects like brightness, contrast, and latent colors could be improvised with the deployment of a novel illumination boost methodology.

The successful conduct of any image enhancement-based projects lies on the acquisition and mastering a few important skillsets/ conceptions. Those are as follows: required level of knowledge in working with MATLAB; C language; C++ Language; Visual C++; Machine Learning; Lighting systems; Remote sensing; Image processing fundamentals; boost methodologies; Data investigation; and several skillsets required for any particular application, for instance, expertise with several imaging techniques like MRI- Magnetic Resonance Imaging, CT- Computed Tomography, etc. needed in case of image processing done from the context of healthcare sector.

7. An X-ray Image Enhancement Algorithm for Dangerous Goods in Airport Security Inspection 

In airports, many people might often carry hazardous objects with/ without knowledge. So, there is a requirement for a robust security inspection system to be placed in the airport for diagnosing any kind of hazardous objects.

The existence of hazardous objects entering the Security Inspection section could be easily recognized by successfully implementing the X-ray-based image improvisation methodology.

The successful conduct of any image enhancement-based projects lies on the acquisition and mastering a few important skillsets/ conceptions. Those are as follows: required level of knowledge in working with MATLAB; basics of X rays; C language; C++ Language; Visual C++; Machine Learning; Security system; Remote sensing; Image processing fundamentals; science behind the hazardous objects; Data investigation; and several skillsets required for any particular application, for instance, expertise with several imaging techniques like MRI- Magnetic Resonance Imaging, CT- Computed Tomography, etc. needed in case of image processing done from the context of healthcare sector.