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Modified BTC algorithm for gray scale images using max-min quantizer

机译:使用最大最小量化器的灰度图像的改进BTC算法

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摘要

With the emerging multimedia technology, image data has been generated at high volume. It is thus important to reduce the image file sizes for storage and effective communication. Block Truncation Coding (BTC) is a lossy image compression technique which uses moment preserving quantization method for compressing digital gray level images. Even though this method retains the visual quality of the reconstructed image with good compression ratio, it shows some artifacts like staircase effect, raggedness, etc. near the edges. A set of advanced BTC variants reported in literature were studied and it was found that though the compression efficiency is good, the quality of the image has to be improved. A modified Block Truncation Coding using max-min quantizer (MBTC) is proposed in this paper to overcome the above mentioned drawbacks. In the conventional BTC, quantization is done based on the mean and standard deviation of the pixel values in each block. In the proposed method, instead of using the mean and standard deviation, an average value of the maximum, minimum and mean of the blocks of pixels is taken as the threshold for quantization. Experimental analysis shows an improvement in the visual quality of the reconstructed image by reducing the mean square error between the original and the reconstructed image. Since this method involves less number of simple computations, the time taken by this algorithm is also very less when compared with BTC.
机译:随着新兴的多媒体技术的出现,图像数据已经大量产生。因此,重要的是减小图像文件的大小以进行存储和有效的通信。块截断编码(BTC)是一种有损图像压缩技术,它使用矩保留量化方法来压缩数字灰度图像。即使此方法以良好的压缩率保留了重建图像的视觉质量,它在边缘附近仍显示出一些伪影,例如阶梯效应,参差不齐等。对文献中报道的一组高级BTC变体进行了研究,发现尽管压缩效率良好,但必须提高图像质量。本文提出了一种使用最大-最小量化器(MBTC)的改进的块截断编码,以克服上述缺点。在传统的BTC中,基于每个块中的像素值的平均值和标准偏差来进行量化。在提出的方法中,代替使用均值和标准差,将像素块的最大,最小和均值的平均值作为量化的阈值。实验分析表明,通过减少原始图像和重建图像之间的均方误差,可以改善重建图像的视觉质量。由于此方法涉及的简单计算数量较少,因此与BTC相比,此算法花费的时间也非常短。

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