  With the increase in multimedia content, the type of distortions associated
with multimedia is also increasing. This problem of image quality assessment is
expanded well in the PIPAL dataset, which is still an open problem to solve for
researchers. Although, recently proposed transformers networks have already
been used in the literature for image quality assessment. At the same time, we
notice that multi-scale feature extraction has proven to be a promising
approach for image quality assessment. However, the way transformer networks
are used for image quality assessment until now lacks these properties of
multi-scale feature extraction. We utilized this fact in our approach and
proposed a new architecture by integrating these two promising quality
assessment techniques of images. Our experimentation on various datasets,
including the PIPAL dataset, demonstrates that the proposed integration
technique outperforms existing algorithms. The source code of the proposed
algorithm is available online: https://github.com/KomalPal9610/IQA
