This paper describes a hardware architectural design of a real-time
counter based entropy coder at a register transfer level (RTL) computing model.
The architecture is based on a lossless compression algorithm called Rice
coding, which is optimal for an entropy range of 1.5 H 2.5 bits per sample.
The architecture incorporates a word-splitting scheme to extend the entropy
coverage into a range of 1.5 H 7.5 bits per sample. We have designed a data
structure in a form of independent code blocks, allowing more robust
compressed bitstream. The design focuses on an RTL computing model and
architecture, utilizing 8-bit buffers, adders, registers, loader-shifters, selectlogics,
down-counters, up-counters, and multiplexers. We have validated the
architecture (both the encoder and the decoder) in a coprocessor for 8
bits/sample data on an FPGA Xilinx XC4005, utilizing 61% of F&G-CLBs, 34%
H-CLBs, 32% FF-CLBs, and 68% IO resources. On this FPGA implementation,
the encoder and decoder can achieve 1.74 Mbits/s and 2.91 Mbits/s throughputs,
respectively. The architecture allows pipelining, resulting in potentially
maximum encoding throughput of 200 Mbit/s on typical real-time TTL
implementations. In addition, it uses a minimum number of register elements. As
a result, this architecture can result in low cost, low energy consumption and
reduced silicon area realizations.