【摘要】：傳統(tǒng)的基于壓縮感知的超分辨率重建算法將圖像看作單尺度,并沒有考慮不同尺度的圖像塊可能包含不同的判別信息.為了有效利用遙感圖像的尺度特性,提出了一種多尺度壓縮感知框架下的遙感圖像超分辨率重建算法.首先通過圖像塊聚類構(gòu)建多尺度訓(xùn)練樣本集,接著運(yùn)用Fisher判別準(zhǔn)則學(xué)習(xí)包含遙感圖像類別信息的判別字典,然后根據(jù)壓縮感知中測(cè)量矩陣的構(gòu)造方式估計(jì)低分辨率圖像的獲取過程,最后結(jié)合判別字典依次重建多尺度模式下的各子區(qū)域圖像.實(shí)驗(yàn)結(jié)果證明了將多尺度壓縮感知引入圖像超分辨率重建的有效性,提出的算法在視覺效果和評(píng)價(jià)指標(biāo)上均優(yōu)于現(xiàn)有的幾種算法.
[Abstract]:The traditional super-resolution reconstruction algorithm based on compression perception regards the image as a single scale and does not consider that the image blocks with different scales may contain different discriminant information. In order to effectively utilize the scale characteristics of remote sensing images, a super-resolution reconstruction algorithm for remote sensing images based on multi-scale compression perception is proposed. Firstly, the multi-scale training sample set is constructed by image block clustering, and then the discriminant dictionary which contains the classification information of remote sensing image is learned by using Fisher discriminant criterion. Then the acquisition process of low-resolution image is estimated according to the construction of measurement matrix in compression perception, and the sub-region images in multi-scale mode are reconstructed in turn by combining the discriminant dictionary. The experimental results demonstrate the effectiveness of introducing multi-scale compression perception into image super-resolution reconstruction. The proposed algorithm is superior to the existing algorithms in terms of visual effect and evaluation index.
【作者單位】： 南京理工大學(xué)計(jì)算機(jī)科學(xué)與工程學(xué)院;
【基金】：國家自然科學(xué)基金項(xiàng)目(61273251) 民用航天技術(shù)“十二五”預(yù)先研究項(xiàng)目(D040201)
【分類號(hào)】：TP751

【相似文獻(xiàn)】

相關(guān)期刊論文 前2條

1 鄒珍軍;孫彥榮;;基于四叉樹理論的人造地物遙感圖像超分辨率技術(shù)方法[J];信息與電腦(理論版);2010年04期

2 ;[J];;年期

相關(guān)碩士學(xué)位論文 前1條

1 王歡;目標(biāo)識(shí)別的遙感圖像超分辨率方法研究[D];哈爾濱師范大學(xué);2014年

，

本文編號(hào)：2361901