Hybrid image inpainting using reproducing kernel Hilbert space and dragonfly inspired wavelet transform

Patil, Balasaheb H.; Patil, Pradeep M.

doi:10.1504/ijnbm.2019.104946

Cited by 2 publications

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“…Patil et al [8] proposed a novel inpainting method which depends on MS modeling, in which the original images are precisely attained by inpainting procedure in the masked image. Now, DWT method is employed to process is the digital images.…”

Section: Literature Reviewmentioning

confidence: 99%

An Efficient Video Inpainting Approach Using Deep Belief Network

Srinivasan¹,

Chinnadurai²

2022

Computer Systems Science and Engineering

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The video inpainting process helps in several video editing and restoration processes like unwanted object removal, scratch or damage rebuilding, and retargeting. It intends to fill spatio-temporal holes with reasonable content in the video. Inspite of the recent advancements of deep learning for image inpainting, it is challenging to outspread the techniques into the videos owing to the extra time dimensions. In this view, this paper presents an efficient video inpainting approach using beetle antenna search with deep belief network (VIA-BASDBN). The proposed VIA-BASDBN technique initially converts the videos into a set of frames and they are again split into a region of 5*5 blocks. In addition, the VIA-BASDBN technique involves the design of optimal DBN model, which receives input features from Local Binary Patterns (LBP) to categorize the blocks into smooth or structured regions. Furthermore, the weight vectors of the DBN model are optimally chosen by the use of BAS technique. Finally, the inpainting of the smooth and structured regions takes place using the mean and patch matching approaches respectively. The patch matching process depends upon the minimal Euclidean distance among the extracted SIFT features of the actual and references patches. In order to examine the effective outcome of the VIA-BASDBN technique, a series of simulations take place and the results denoted the promising performance.

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Section: Literature Reviewmentioning

confidence: 99%

An Efficient Video Inpainting Approach Using Deep Belief Network

Srinivasan¹,

Chinnadurai²

2022

Computer Systems Science and Engineering

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Effect of Optimized Deep Belief Network to Patch-Based Image Inpainting Forensics

Patil

2022

International Journal of Swarm Intelligence Research

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This paper intends to propose a new model for detecting the patch based inpainting operation using Enhanced Deep Belief Network (E-DBN). The proposing model makes strong supervising of DBN that will capture the manipulated information. In fact, the enhancement is done under optimization concept, where the activation function and weight of DBN is optimally tuned by a new hybrid algorithm termed as Swarm Mutated Lion Algorithm (SM-LA). The hybridization model combines two conventional models: Group Search Optimizer (GSO) and Lion Algorithm (LA). Finally, the performance of proposed model is compared over other conventional models with respect to certain performance measures.

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Hybrid image inpainting using reproducing kernel Hilbert space and dragonfly inspired wavelet transform

Cited by 2 publications

References 0 publications

An Efficient Video Inpainting Approach Using Deep Belief Network

An Efficient Video Inpainting Approach Using Deep Belief Network

Effect of Optimized Deep Belief Network to Patch-Based Image Inpainting Forensics

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