Image enhancement is one of the important part of image processing. Proposed research presents an image enhancement method, named CLAHE-HWT derived from its existing CLAHE-DWT, which combines the Contrast Limited Adaptive Histogram Equalization (CLAHE) with Hybrid Wavelet Transform Type I (HWT I) wavelets. The method includes, the original image is decomposed into low-frequency and high-frequency components by HWT I. Then, the low-frequency coefficients is enhanced using CLAHE and the high-frequency coefficients kept unchanged to limit noise enhancement. Finally, the image is reconstructed by taking inverse HWT of the new coefficients. In order to counteract over-enhancement, the recreated and original images are averaged using an originally proposed weighting factor. Two orthogonal transforms combine to form a hybrid wavelet. Here different orthogonal transforms are used like Kekre, Walsh, Cosine, Hartley and Haar in 5 × 4 combinations total 20 hybrid wavelets of type I. This research compares all the 20 combinations of HWT I to find out the best combination of HWT with CLAHE. Experimental results demonstrate CLAHE-HWT shows better results for noise depression and avoid over enhancement.