东南大学学报（英文版）
東南大學學報（英文版）
동남대학학보（영문판）
JOURNAL OF SOUTHEAST UNIVERSITY
2010年
3期
457-460
,共4页
超分辨率%梯度残差项%数据残差项%车牌%正则性
超分辨率%梯度殘差項%數據殘差項%車牌%正則性
초분변솔%제도잔차항%수거잔차항%차패%정칙성
super-resolution%residual gradient term%residual data term%license plate%regularization
为了改善实际交通环境中运动车辆车牌图像的质量,提出一种新的超分辨率重建方法,即通过融合低分辨率图像间的互补信息得到一幅高分辨率车牌图像.首先,在超分辨率重建正则化框架下引入梯度残差项作为一个梯度强制项来改善重建图像的质量.其次,为了提高重建算法的鲁棒性,用L1范数度量数据残差项和梯度残差项.最后,用最速下降法求解相应的最小能量泛函.模拟和实际视频图像序列的实验结果验证了所提方法的有效性和实用性,所提方法在重建图像的信噪比指标和视觉效果方面均优于双三次插值和DAMRF法.
為瞭改善實際交通環境中運動車輛車牌圖像的質量,提齣一種新的超分辨率重建方法,即通過融閤低分辨率圖像間的互補信息得到一幅高分辨率車牌圖像.首先,在超分辨率重建正則化框架下引入梯度殘差項作為一箇梯度彊製項來改善重建圖像的質量.其次,為瞭提高重建算法的魯棒性,用L1範數度量數據殘差項和梯度殘差項.最後,用最速下降法求解相應的最小能量汎函.模擬和實際視頻圖像序列的實驗結果驗證瞭所提方法的有效性和實用性,所提方法在重建圖像的信譟比指標和視覺效果方麵均優于雙三次插值和DAMRF法.
위료개선실제교통배경중운동차량차패도상적질량,제출일충신적초분변솔중건방법,즉통과융합저분변솔도상간적호보신식득도일폭고분변솔차패도상.수선,재초분변솔중건정칙화광가하인입제도잔차항작위일개제도강제항래개선중건도상적질량.기차,위료제고중건산법적로봉성,용L1범수도량수거잔차항화제도잔차항.최후,용최속하강법구해상응적최소능량범함.모의화실제시빈도상서렬적실험결과험증료소제방법적유효성화실용성,소제방법재중건도상적신조비지표화시각효과방면균우우쌍삼차삽치화DAMRF법.
A novel reconstruction method to improve the recognition of license plate texts of moving vehicles in real traffic videos is proposed, which fuses complimentary information among low resolution (LR) images to yield a high resolution (HR) image. Based on the regularization super-resolution (SR) reconstruction schemes, this paper first introduces a residual gradient (RG) term as a new regularization term to improve the quality of the reconstructed image. Moreover, L1 norm is used to measure the residual data (RD) term and the RG term in order to improve the robustness of the proposed method. Finally, the steepest descent method is exploited to solve the energy functional. Simulated and real acquired video sequence experiments show the effectiveness and practicability of the proposed method and demonstrate its superiority over the bi-cubic interpolation and discontinuity adaptive Markov random field (DAMRF) SR method in both signal to noise ratios (SNR) and visual effects.
