Combination of Gabor and Butterworth filters in fast fourier transform algorithm for fabric image enhancement

Fabric is a prominent material that is used and will continuously be used in the textile field. The studies on fabrics may involve the production of fabrics, the usage of fabrics, the defects of fabrics, and the reactions of fabrics to obstacles. This research implements the combination of Gabor and Butterworth filters in the Fast Fourier Transform algorithm on fabric images to study how they react to obstacles or image noise. A filter acts as a medium in image processing techniques as it can enhance input images, hence improving the results for further processing such as image segmentation. The aim of this research is to investigate and analyse the different effects of combining the Gabor and Butterworth High-pass Filter or Gabor and Butterworth Low-pass Filter on fabric images. All algorithms will be implemented using MATLAB R2018B. Evaluations of the results are by visual examination and by calculating the Peak Signal-to-Noise Ratio (PSNR) value. The results showed that the combination of the Gabor and Butterworth High-pass Filter produced better noise removal ability, which is supported by high values of PSNR.