TY  - JOUR
AU  - Danyal, Mian Muhammad
AU  - Samin, Omar Bin
AU  - Khan, Sarwar Shah
AU  - Khan, Sajid
PY  - 2025
DA  - 2025/06/26
TI  - Multi Focus Image Fusion using Image Enhancement Methods
JO  - ICCK Journal of Image Analysis and Processing
T2  - ICCK Journal of Image Analysis and Processing
JF  - ICCK Journal of Image Analysis and Processing
VL  - 1
IS  - 2
SP  - 57
EP  - 72
DO  - 10.62762/JIAP.2025.772403
UR  - https://www.icck.org/article/abs/JIAP.2025.772403
KW  - image fusion
KW  - multifocus images
KW  - discrete cosine transform
KW  - high boost filter
KW  - discrete wavelet transform
KW  - marr--hildreth edge detection
AB  - The challenge with multifocus images lies in different regions being in focus across various shots, resulting in some areas appearing blurry while others are sharp. This issue is prevalent in fields such as medical imaging, remote sensing, and photography, where clear and detailed images are essential. This project introduces a novel approach to multifocus image fusion by integrating the Marr--Hildreth edge detection technique with Discrete Cosine Transform (DCT), Stationary Wavelet Transform (SWT), and Discrete Wavelet Transform (DWT). The Marr--Hildreth algorithm detects edges by identifying zero-crossings in the Laplacian of a Gaussian-blurred image, effectively highlighting areas with significant intensity changes. The proposed method was evaluated across four datasets--clocks, leaves, balloons, and bottles. Performance metrics such as Peak Signal-to-Noise Ratio (PSNR), Root Mean Square Error (RMSE), Mean Absolute Error (MAE), and Entropy indicated that this integrated approach significantly enhances image quality. By combining Marr--Hildreth edge detection with DCT, SWT, and DWT, the method improves image clarity and detail, offering a promising advancement in image fusion techniques. This innovative approach not only addresses multifocus image challenges but also paves the way for further developments in image fusion processes. The study suggests that enhanced image processing techniques can be applied across various fields requiring high-quality image fusion.
SN  - 3068-6679
PB  - Institute of Central Computation and Knowledge
LA  - English
ER  - 

@article{Danyal2025Multi,
  author = {Mian Muhammad Danyal and Omar Bin Samin and Sarwar Shah Khan and Sajid Khan},
  title = {Multi Focus Image Fusion using Image Enhancement Methods},
  journal = {ICCK Journal of Image Analysis and Processing},
  year = {2025},
  volume = {1},
  number = {2},
  pages = {57-72},
  doi = {10.62762/JIAP.2025.772403},
  url = {https://www.icck.org/article/abs/JIAP.2025.772403},
  abstract = {The challenge with multifocus images lies in different regions being in focus across various shots, resulting in some areas appearing blurry while others are sharp. This issue is prevalent in fields such as medical imaging, remote sensing, and photography, where clear and detailed images are essential. This project introduces a novel approach to multifocus image fusion by integrating the Marr--Hildreth edge detection technique with Discrete Cosine Transform (DCT), Stationary Wavelet Transform (SWT), and Discrete Wavelet Transform (DWT). The Marr--Hildreth algorithm detects edges by identifying zero-crossings in the Laplacian of a Gaussian-blurred image, effectively highlighting areas with significant intensity changes. The proposed method was evaluated across four datasets--clocks, leaves, balloons, and bottles. Performance metrics such as Peak Signal-to-Noise Ratio (PSNR), Root Mean Square Error (RMSE), Mean Absolute Error (MAE), and Entropy indicated that this integrated approach significantly enhances image quality. By combining Marr--Hildreth edge detection with DCT, SWT, and DWT, the method improves image clarity and detail, offering a promising advancement in image fusion techniques. This innovative approach not only addresses multifocus image challenges but also paves the way for further developments in image fusion processes. The study suggests that enhanced image processing techniques can be applied across various fields requiring high-quality image fusion.},
  keywords = {image fusion, multifocus images, discrete cosine transform, high boost filter, discrete wavelet transform, marr--hildreth edge detection},
  issn = {3068-6679},
  publisher = {Institute of Central Computation and Knowledge}
}