Edge-Guided Image Gap Interpolation Using Multi-Scale Transformation

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F60461373%3A22340%2F16%3A43901643" target="_blank" >RIV/60461373:22340/16:43901643 - isvavai.cz</a>

Nalezeny alternativní kódy

RIV/68407700:21730/16:00306283

Výsledek na webu

<a href="http://ieeexplore.ieee.org/document/7511757/" target="_blank" >http://ieeexplore.ieee.org/document/7511757/</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/TIP.2016.2590825" target="_blank" >10.1109/TIP.2016.2590825</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Edge-Guided Image Gap Interpolation Using Multi-Scale Transformation

Popis výsledku v původním jazyce

This paper presents improvements in image gap restoration through the incorporation of edge-based directional interpolation within multi-scale pyramid transforms. Two types of image edges are reconstructed: 1) the local edges or textures, inferred from the gradients of the neighboring pixels and 2) the global edges between image objects or segments, inferred using a Canny detector. Through a process of pyramid transformation and downsampling, the image is progressively transformed into a series of reduced size layers until at the pyramid apex the gap size is one sample. At each layer, an edge skeleton image is extracted for edge-guided interpolation. The process is then reversed; from the apex, at each layer, the missing samples are estimated (an iterative method is used in the last stage of upsampling), up-sampled, and combined with the available samples of the next layer. Discrete cosine transform and a family of discrete wavelet transforms are utilized as alternatives for pyramid construction. Evaluations over a range of images, in regular and random loss pattern, at loss rates of up to 40%, demonstrate that the proposed method improves peak-signal-to-noise-ratio by 1-5 dB compared with a range of best published works.

Název v anglickém jazyce

Edge-Guided Image Gap Interpolation Using Multi-Scale Transformation

Popis výsledku anglicky

This paper presents improvements in image gap restoration through the incorporation of edge-based directional interpolation within multi-scale pyramid transforms. Two types of image edges are reconstructed: 1) the local edges or textures, inferred from the gradients of the neighboring pixels and 2) the global edges between image objects or segments, inferred using a Canny detector. Through a process of pyramid transformation and downsampling, the image is progressively transformed into a series of reduced size layers until at the pyramid apex the gap size is one sample. At each layer, an edge skeleton image is extracted for edge-guided interpolation. The process is then reversed; from the apex, at each layer, the missing samples are estimated (an iterative method is used in the last stage of upsampling), up-sampled, and combined with the available samples of the next layer. Discrete cosine transform and a family of discrete wavelet transforms are utilized as alternatives for pyramid construction. Evaluations over a range of images, in regular and random loss pattern, at loss rates of up to 40%, demonstrate that the proposed method improves peak-signal-to-noise-ratio by 1-5 dB compared with a range of best published works.

Druh

J_x - Nezařazeno - Článek v odborném periodiku (Jimp, Jsc a Jost)

CEP obor

JD - Využití počítačů, robotika a její aplikace

OECD FORD obor

—

Projekt

—

Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2016

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

IEEE Transactions on Image Processing

ISSN

1057-7149

e-ISSN

—

Svazek periodika

25

Číslo periodika v rámci svazku

9

Stát vydavatele periodika

US - Spojené státy americké

Počet stran výsledku

12

Strana od-do

4394-4405

Kód UT WoS článku

000381436200008

EID výsledku v databázi Scopus

2-s2.0-84984868165