Contrast illumination of Magnetic Resonance (MR) and Computed Tomography (CT) images at local regions is low, and edge overlapping for various tissues in imaging is higher. In this paper, a novel medical image enhancement method dedicated to overcoming the problem stated above is proposed by investigating Double Density Wavelet Transform (DDWT) and Stationary Wavelet Transform (SWT). The process is followed by a new enhanced contrast, illumination module, and linear combination strategy. DDWT decomposes the original image, and the Inverse Discrete Wavelet Transform (IDWT) computes the reconstructed image. SWT again decomposes the original image at four sub-bands including LL, LH, HL, and HH. The suggested statistical module is then applied to the low-frequency subband (LL) for improving the contrast and illumination region of interest (ROI) and incorporated with high-frequency sub-bands by Inverse SWT (ISWT). Finally, the linear combination was obtained for the resulting enhanced image to maintain the illumination for the details of the image. The proposed algorithm was verified with various datasets and validated for not only subjective but objective evaluation as well. It exhibited high performance for contrast and brightness suitable for diagnostic purposes.