A histogram is a common graphical descriptor to represent features of distribution of pixels in an image. However, for most of the applications that apply histograms, the time complexity of histogram construction is much higher than that of the other parts of the applications. Hence, column histograms had been presented to construct the local histogram in constant time. In order to increase its performance, this letter proposes a linked-list histogram to avoid generating empty bins, further using hash tables with bin entries to map pixels. Experimental results demonstrate the effectiveness of the proposed method and its superiority to the state-of-the-art method.

Embedded systems are constrained by the available memory, and code-compression techniques address this issue by reducing the code size of application programs. The main challenge for the development of an effective code-compression technique is to reduce code size without affecting the overall system performance. Dictionary-based code-compression schemes are the most commonly used code-compression methods, because they can provide both good compression ratio and fast decompression. We propose an XOR-based reference scheme that can enhance the compression ratio on all the existing dictionary-based algorithms by changing the distribution of the symbols. Our approach works on all kinds of computer architecture with fixed length instructions, such as RISC or VLIW. Experiments show that our approach can further improve the compression ratio with nearly no hardware, performance, and power overheads.