Symmetric residue pyramids - an extension of Burt Laplacian pyramids

Rakshit, Subrata; Nema, Malay Kumar

doi:10.1109/icassp.2003.1199470

Cited by 9 publications

(4 citation statements)

References 5 publications

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“…Another method -Symmetric Residue Pyramids [4] was proposed as an extension to Burt Laplacian pyramids. This extension of the Laplacian pyramid exploits the redundancy present in the Laplacian pyramid to achieve better signal compaction and non redundant edge representation.…”

Section: Figure 2 Shows Laplacian Generation Methodsmentioning

confidence: 99%

Super Resolution of Video with Sharpened Edges Using Multiple Frames -- A Novel Approach

Pais

D'Souza

Reddy

et al. 2009

2009 International Conference on Advances in Recent Technologies in Communication and Computing

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In most electronic video applications, video with Higher Resolution(HR) are often required. HR video can offer more details that may be critical in various applications like Video Surveillance. Super resolution technique refers to generation of high resolution image from low resolution image by adding some extra information. Super resolution allows us to reduce the need of extra hardware to obtain HR image. This paper proposes a new method for super resolution video generation with sharpened edges using multiple frames. Unique information present in subpixel shifted frames is extracted and used for frequency domain registration process.

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Section: Figure 2 Shows Laplacian Generation Methodsmentioning

confidence: 99%

Super Resolution of Video with Sharpened Edges Using Multiple Frames -- A Novel Approach

Pais

D'Souza

Reddy

et al. 2009

2009 International Conference on Advances in Recent Technologies in Communication and Computing

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“…Compute the edge representation (L 21 ) of the reference image f p by Symmetric Residue Pyramid (SRP) method. 37 Step 8. Apply sharpness enhancement on the edge representation (L 21 ) by unsharp method.…”

Section: Sr Based On Multiple Framesmentioning

confidence: 99%

Super-resolution video generation algorithm for surveillance applications

Pais¹,

D'Souza²,

Reddy³

2013

The Imaging Science Journal

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Video surveillance is one of the major applications where high-resolution (HR) images are crucial. Since the video camera has limited spatial and temporal resolution, there is a need for super resolution video generation algorithms. In this paper, we have presented a novel technique for activity detection in the surveillance video. To achieve this goal, we have proposed and investigated efficient algorithms for Video Object Plane (VOP) generation, shadow removal from VOP and super-resolved VOP generation, for activity detection from surveillance video. The proposed VOP generation algorithm is computationally efficient and works for both dynamic and static backgrounds. The novel shadow removal algorithm for the VOP is based on texture and its performance has been studied based on average shadow detection and discrimination rates. The proposed super-resolution video generation algorithm has been designed using edge models. The performance of this algorithm has been evaluated using a numerical analysis technique and is found to be better than bi-cubic and bi-linear interpolation techniques.

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“…Symmetric Residue Pyramids [14] were proposed as an extension to Burt Laplacian pyramids. Initial aim of the SRP was to achieve better signal compaction.…”

Section: Symmetric Residue Pyramidsmentioning

confidence: 99%

“…A model-based description is convenient for altering the sharpness of selected edges without affecting the resolution or frequency content of the image as a whole. Another result of relevance to the present work is the extension of Burt's Laplacian pyramids called Symmetric Residue pyramids [14] (SRP). It addresses the issue of consistency between pyramid subbands and the nature of independent information at each level.…”

Section: Introductionmentioning

confidence: 99%

Edge Model Based High Resolution Image Generation

Nema

Rakshit

Chaudhuri

2006

Computer Vision, Graphics and Image Processing

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Abstract. The present paper proposes a new method for high resolution image generation from a single image. Generation of high resolution (HR) images from lower resolution image(s) is achieved by either reconstruction-based methods or by learning-based methods. Reconstruction based methods use multiple images of the same scene to gather the extra information needed for the HR. The learning-based methods rely on the learning of characteristics of a specific image set to inject the extra information for HR generation. The proposed method is a variation of this strategy. It uses a generative model for sharp edges in images as well as descriptive models for edge representation. This prior information is injected using the Symmetric Residue Pyramid scheme. The advantages of this scheme are that it generates sharp edges with no ringing artefacts in the HR and that the models are universal enough to allow usage on wide variety of images without requirement of training and/or adaptation. Results have been generated and compared to actual high resolution images.

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Symmetric residue pyramids - an extension of Burt Laplacian pyramids

Cited by 9 publications

References 5 publications

Super Resolution of Video with Sharpened Edges Using Multiple Frames -- A Novel Approach

Super Resolution of Video with Sharpened Edges Using Multiple Frames -- A Novel Approach

Super-resolution video generation algorithm for surveillance applications

Edge Model Based High Resolution Image Generation

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