PROJECT TITLE :

Single Image Reflection Removal Using Convolutional Neural Networks

ABSTRACT:

Specular reflection occurs when individuals photograph through glass, obscuring the view behind the glass. Most investigations have focused on recovering the transmitted scene from many photos rather than a single image because of the ease of implementation. It's not practicable for most people to use numerous photographs in real life because of the key shooting conditions. Single-image reflection reduction is proposed using convolutional neural networks in this paper. As a result of our ghosting model, acquired photographs have a reflective quality to them. Ghosting and relative intensity are used to create multiple-reflection pictures from a single image. Encoder and decoder are then built into a complete end-to-end network We employ a combined training technique to learn layer separation information from the synthesised reflection pictures in order to optimise the network parameters. Both internal and external losses are taken into account when optimising the loss function. This network is then used to remove a single image's reflection. The proposed solution does not necessitate the use of handcrafted features or specular filters to remove reflections. For both synthetic and real photos, the suggested method is able to successfully eliminate reflections from both images, as well as achieve the top scores in peak SNR, structural similarity and feature similarities.


Did you like this research project?

To get this research project Guidelines, Training and Code... Click Here


PROJECT TITLE : A Siamese Content-Attentive Graph Convolutional Network For Personality Recognition Using Physiology ABSTRACT: Affective multimedia information has long been employed as a source of stimulation in the study
PROJECT TITLE : Convolutional Recurrent Neural Networks for Glucose Prediction ABSTRACT: Blood glucose control is critical for diabetes management. Machine learning techniques are used in current digital therapy approaches for
PROJECT TITLE : 3D APA-Net 3D Adversarial Pyramid Anisotropic Convolutional Network for Prostate Segmentation in MR Images ABSTRACT: Diagnostic and treatment of prostate illnesses, particularly cancer, rely heavily on accurate
PROJECT TITLE : Progressively Trained Convolutional Neural Networks for Deformable Image Registration ABSTRACT: The quick registration periods of deep learning-based algorithms for deformable picture registration make them viable
PROJECT TITLE : Deep Color Guided Coarse-to-Fine Convolutional Network Cascade for Depth Image Super-Resolution ABSTRACT: The task of super-resolution of depth images is both significant and difficult. In order to deal with this

Ready to Complete Your Academic MTech Project Work In Affordable Price ?

Project Enquiry