【摘要】：在圖像對比度增強(qiáng)算法中,結(jié)合自適應(yīng)直方圖均衡化和對比度受限兩項(xiàng)技術(shù)的對比度受限自適應(yīng)直方圖均衡化算法(CLAHE)是一種常用的低對比度圖像增強(qiáng)算法。為了解決快速診斷試劑中的過敏原檢測試紙條圖像對比度低的問題,嘗試給出一種改進(jìn)的CLAHE圖像增強(qiáng)新算法。新算法在傳統(tǒng)的CLAHE算法的基礎(chǔ)上,通過引入一個(gè)自適應(yīng)參數(shù)T來自動調(diào)整圖像每個(gè)子塊的像素點(diǎn)重新分配的范圍,從而達(dá)到增強(qiáng)圖像細(xì)節(jié)的目的。通過對過敏原檢測試紙條圖像增強(qiáng)的實(shí)驗(yàn)對比分析,表明改進(jìn)后的CLAHE算法可有效地改善該類醫(yī)學(xué)試紙條圖像的增強(qiáng)視覺效果,為后續(xù)醫(yī)學(xué)試紙條的分割和識別奠定基礎(chǔ)。與此同時(shí),以圖像均方根對比度為定量統(tǒng)計(jì)依據(jù),與傳統(tǒng)CLAHE算法的結(jié)果比較得出:改進(jìn)的CLAHE算法明顯提高圖像均方根對比度,傳統(tǒng)的CLAHE算法平均提高原圖像均方根對比度1~2倍,而改進(jìn)的CLAHE算法平均提高3~4倍,進(jìn)一步驗(yàn)證新算法是一種對過敏原檢測試紙條圖像增強(qiáng)更為有效的方法。
[Abstract]:In the image contrast enhancement algorithm, the contrast constrained adaptive histogram equalization algorithm (CLAHE), which combines adaptive histogram equalization and contrast restriction, is a commonly used low contrast image enhancement algorithm. In order to solve the problem of low contrast of strip image in allergen test in rapid diagnostic reagent, an improved CLAHE image enhancement algorithm was proposed. On the basis of the traditional CLAHE algorithm, the new algorithm automatically adjusts the range of pixel redistribution of each sub-block of the image by introducing an adaptive parameter T, so as to enhance the details of the image. Through the experimental comparative analysis of strip image enhancement of allergen test strip, it is shown that the improved CLAHE algorithm can effectively improve the visual effect of this kind of medical test strip image, and lay a foundation for the segmentation and recognition of subsequent medical test strip. At the same time, based on the quantitative statistical basis of image root mean square contrast, compared with the results of traditional CLAHE algorithm, the improved CLAHE algorithm obviously improves the image root mean square contrast, the traditional CLAHE algorithm increases the root mean square contrast of the original image by 1 鈮，

本文編號：2523773