Various image transformations can be used to compress images, to reduce noises in images and to extract useful features. Watermarking techniques using DCT and DWT have been a lot of research interest in the spread of multimedia contents. In this paper, Gabor cosine and sine transform considered as human visual filter is applied to embedding and extraction of watermarks for digital images. The proposed transform is used for watermarking with fifteen attacks. Randomly normal distributed noises are used as an embedded watermark. To measure the similarity between the embedded watermark and extracted one, a correlation value is computed and furthermore is compared with that of existing DCT method. Correlation values of extracted watermark are computed with randomly normal distributed noise sequences, and the sequence with the largest correlation value is declared as the embedded watermark. Frequency components are divided into various bands. Experimental results for low frequency and mid-frequency bands have shown that the proposed GCST provides a good watermarking algorithm and its performance is better than DCT.