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.