We describe here a digital image restoration technique for image data degraded by an a-priori known blur function. To be more specific, we are interested in processing digital image data, obtained using coherent illumination (either optical or microwaves), that has been degraded by a known blur factor, The complex valued image i (amplitude) is related to the measured blurred data i by i = i * b, where * denotes convolution and b is a known complex-valued blur function. An inverse filtering technique is traditionally used in the Fourier domain. But, for some image analysis applications, a more direct, deblurring approach in the image domain may be more desirable. An illustrative possible scenario is given by an image interpreter looking at a small portion of some blurred image. In this case a direct deblurring method applied to the selected image area might be more flexible. We present here a direct image plane deconvolution method using reasonably short length convolution kernels. In the more specific case of quadratic phase-type blurs, a direct image plane Fresnel transform approach is also discussed.