This paper presents the Cameron Project, which aims to provide a high level, algorithmic language and optimizing compiler for the development of image processing applications on Reconfigurable Computing Systems (RCSs). SA-C, a single assignment variant of the C programming language, is designed to exploit both coarse-grain and fine-grain parallelism in image processing applications. Khoros, a software development environment commonly used for image processing, has been modified to support SA-C program development.SA-C supports image processing with true multidimensional arrays, and with sophisticated array access and windowing mechanisms. Reduction operators such as medians and histograms are also provided. The optimizing compiler targets RCSs, which are fine-grained parallel processors made up of Field Programmable Gate Arrays (FPGAs), memories and interconnection hardware. They can be used as inexpensive co-processors with conventional workstations or PCs. This paper discusses compiler optimizations to generate optimal FPGA code using dataflow analysis techniques applied to data dependence graphs. Initial results are presented.