CAJ | 학술논문

色彩空间转换在图像采集、显示，色彩信息传递及重现中发挥着重要作用，为实现真正意义上的“所见即所得”，需提高色彩转换精度。针对传统色彩空间转换模型中BP神经网络转换精度低、易陷入局部最优等不足，使用萤火虫算法优化BP神经网络的初始权值和阈值，提出一种FABPNN算法的色彩空间转换模型，并使用色差模型进行验证。实验结果表明，该模型具有较高的色彩转换精度，达到预期效果。
색채공간전환재도상채집、현시，색채신식전체급중현중발휘착중요작용，위실현진정의의상적“소견즉소득”，수제고색채전환정도。침대전통색채공간전환모형중BP신경망락전환정도저、역함입국부최우등불족，사용형화충산법우화BP신경망락적초시권치화역치，제출일충FABPNN산법적색채공간전환모형，병사용색차모형진행험증。실험결과표명，해모형구유교고적색채전환정도，체도예기효과。
Color space conversion has become a very important role in the image acquisition ,display and the transmission of the color information in the replication .In order to achieve a real sense of "What you see is what you get ."need to be fur‐ther studied on the model of color space conversion ,improve the color conversion accuracy .In view of the traditional color space conversion model of BPNN in the conversion of low precision ,easily falling into local optimum problems ,using the firefly algorithm to optimize BPNN's initial weights and thresholds ,proposed a FABPNN algorithm for color space conver‐sion model and verified using the color difference model .Experimental results table name the model has a high color con‐version accuracy ,can achieve the desired effect .