Automated hardware design from behavior-level abstraction has drawn wide interest in FPGA-based acceleration and configurable computing research field. However, for many high-level programming languages, such as C/C++, the description of bitwise access and computation is not as direct as hardware description languages, and high-level synthesis of algorithmic descriptions may generate suboptimal implementations for bitwise computation-intensive applications. In this paper we introduce a bit-level transformation and optimization approach to assisting high-level synthesis of algorithmic descriptions. We introduce a bit-flow graph to capture bit-value information. Analysis and optimizing transformations can be performed on this representation, and the optimized results are transformed back to the standard data-flow graphs extended with a few instructions representing bitwise access. This allows high-level synthesis tools to automatically generate circuits with higher quality. Experiments show that our algorithm can reduce slice usage by 29.8% on average for a set of real-life benchmarks on Xilinx Virtex-4 FPGAs. In the meantime, the clock period is reduced by 13.6% on average, with an 11.4% latency reduction. In addition, the synthesized accelerating modules can achieve up to 2900X performance speedup over an embedded PowerPC microprocessor.