Online Store - 8925533488 /89

Chennai - 8925533480 /81

Hyderabad - 8925533482 /83

Vijayawada -8925533484 /85

Covai - 8925533486 /87

Image Dehazing by An Artificial Image Fusion Method based on Adaptive Structure Decomposition

( 0 Rating )
Shape Image One
0 student

Abstract:

The project presents visibility restoration of single hazy images using color analysis and depth estimation with enhanced refined transmission technique. Visibility of outdoor images is often degraded by turbid mediums in poor weather, Haze can seriously affect the visible and visual quality of outdoor images. As a challenge in practice, image dehazing techniques are always used to remove haze from the captured images. Existing image dehazing algorithms focus on enhancing both global image contrast and saturation, but ignore the local enhancement. So the dehazed images do not often have good performance in the visual quality of local details. This paper proposes a new single-image dehazing solution based on the adaptive structure decomposition integrated multi-exposure image fusion A set of underexposed image sequences are extracted from a single blurred image first by a series of gamma correction and the spatial linear adjustment of saturation. Then different exposure-level images are fused into a haze-free image by applying a multi-exposure image fusion scheme based adaptive structure decomposition to each image patch. The proposed image dehazing scheme can effectively eliminate the visual degradation caused by haze without the physical model inversion of haze formation. Both apriori estimation of scene depth and the expensive refinement process of depth mapping can be avoided. The entropy of image texture named as texture energy is used to measure the image energy and obtain the information size contained in an image. Meanwhile, a texture energy based method is presented to adaptively select the corresponding patch size for the decomposition of image structure. In addition, this paper verifies that the dehazed images obtained by the patch based always meet the requirements of intensity decrease. The comparative experiment results are evaluated in both qualitative and quantitative aspects, which confirm the effectiveness of the proposed solution in haze removal.

 

Existing Method:

  •  Additional Information approaches
  • Retinex theory and Gamma correction
  • Local contrast adjustment technique
  • Dark channel prior method

 

Drawbacks:

  • Difficult to acquire scene depth information
  • Low performance in restoration of image quality
  • It degrades image quality after restoration due to blocking artifacts.
  • It doesn’t provide optimal transmission which causes halo effect and color distortion problems

 

Proposed Method:

  •  Visibility Restoration of single hazy images based on,
  • Color Analysis and Depth Estimation with Enhanced refined transmission
  • Fusion algorithm

 

 Block Diagram:

Image Dehazing by An Artificial Image Fusion Method

 

Methodologies:

  •  Depth Estimation
  • Adaptive Gamma Correction
  • Color Analysis
  • Visibility Restoration

 

Advantages:

  • It avoids halo effect and insufficient transmission estimation problems.
  • It recovers better image quality under various weather condition changes.
  • Less algorithm complexity.
  • Its processing time is low.

Applications:

  •  Advanced Driver Assistance System
  • Video Surveillance systems
  • Obstacle Detection systems
  • Outdoor Object recognition systems

Software Requirement:

  •  MATLAB 2014 version
Curriculum is empty

pantech team

Agile Project Expert

Course Rating

0.00 average based on 0 ratings

Star
0%
Star
0%
Star
0%
Star
0%
Star
0%
Course Preview
  • Price
    Free
  • Instructor pantech team
  • Duration 15 Hrs
  • Enrolled 0 student
  • Access 3 Months

More Things You Might Like This

Free

Student Performance Prediction using Machine Learning

Abstract: Although the educational level of the Portuguese population has improved in the last decades, the statistics keep Portugal at Europe’s tail end due to its high student failure rates. In particular, lack of success in the core classes of Mathematics and the Portuguese language is extremely serious. On the other hand, the fields of

Free

Student feedback analysis

Abstract: Advances in natural language processing (NLP) and educational technology, as well as the availability of unprecedented amounts of educationally-relevant text and speech data, have led to an increasing interest in using NLP to address the needs of teachers and students. Educational applications differ in many ways, however, from the types of applications for which

Free

Machine Learning based Regression Model for Prediction of Soil Surface Humidity over Moderately Vegetated Fields

Abstract: Agriculture is one of the major revenue producing sectors of India and a source of survival. Numerous seasonal, economic and biological patterns influence the crop production but unpredictable changes in these patterns lead to a great loss to farmers. These risks can be reduced when suitable approaches are employed on data related to soil

Open Whatsapp Chat
Need Any Help?
Hello
Welcome to Pantech eLearning!..

How can i help you?