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摘要
In the application of image compression, to generate effective common bitmap and reduce the distortion risk of color image compressed by single bitmap block truncation coding while remaining compression ratio, a single bitmap block truncation coding method based on binary fireworks algorithm is proposed. First, the color image was divided into non-overlapping blocks, and the initial bitmap of each block was generated by the weight plane method. Then, the positions that need to be optimized in the initial bitmap of each sub-image block were determined by two different strategies, and the values of these positions were used as the initial values of the fireworks algorithm. Next, the fireworks algorithm was changed to binary form and optimized to generate a common bitmap and six quantization values for each block. Finally, each block was restored according to the common bitmap and the quantization values, and the color image was reconstructed by the restored blocks. Through the experiments on the test images, the proposed method was compared with three reference methods from the aspects of the detailed visual effects of the compressed images, the mean square error, and the structural similarity between the compressed images and the original images. Results show that the common bitmap generated by the proposed method was effective, and the global optimization strategy was better than the local optimization strategy. The mean values of the mean square errors between the compressed images generated by the global optimization strategy and the original images were 56.939 7 and 106.317 4 when the block size was 4×4 and 8×8, which were lower than those of the three reference methods. The mean values of the structural similarity index values between the compressed images generated by the global optimization strategy and the original images were 0.968 2 and 0.943 1 when the block size was 4×4 and 8×8, which were higher than those of the three reference methods. It indicates that the similarity between the compressed images generated by the proposed method and the original images is higher, and the accuracy of the compressed images is effectively improved while maintaining the compression ratio.
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