基于直方图均衡的空间需求优化方法

为了解决平台法直方图增强算法中出现的“斑块”问题,提出了基于统计与累积空间复用和无损压缩统计的方法。经理论分析和实验验证,新算法对内存的需求比经典直方图均衡降低85%以上,且时间复杂度与经典直方图均衡算法相比属于同一量级。结果表明,此优化方法将平台法直方图均衡所需的处理空间进行了大幅度压缩,解决了红外实时成像系统中因处理芯片运行内存不足而导致算法难以实现的问题,较好地达到了实际应用要求。

Optimized method for space requirements based on histogram equalization

In order to solve the“mosaic”problem in plateau histogram enhancement algorithms, a novel method was proposed based on statistics, reuse of accumulated space and lossless compression. After theoretical analysis and simulation, the new algorithm reduces memory requirement more than 85%, but the time complexity keeps the same level as the original plateau histogram equalization. As a result, the processing space of plateau histogram equalization is greatly compressed by this improved algorithm, the difficulty of algorithm realization caused by the shortage of running memory of operating chips in infrared real time imaging system is solved and the requirements of practical application are achieved.