  Deconvolution is essential for radio interferometric imaging to produce
scientific quality data because of finite sampling in the Fourier plane. Most
deconvolution algorithms are based on CLEAN which uses a grid of image pixels,
or clean components. A critical matter in this process is the selection of
pixel size for optimal results in deconvolution. As a rule of thumb, the pixel
size is chosen smaller than the resolution dictated by the interferometer. For
images consisting of unresolved (or point like) sources, this approach yields
optimal results. However, for sources that are not point like, in particular
for partially resolved sources, the selection of right pixel size is still an
open issue. In this paper, we investigate the limitations of pixelization in
deconvolving extended sources. In particular, we pursue the usage of
orthonormal basis functions to model extended sources yielding better results
than by using clean components.
