Bit Allocation Strategy Based on Psychovisual Threshold in Image Compression

• Main Authors: Ernawan, Ferda, M. Nomani, Kabir, Jasni, Mohamad Zain
• Format: Article
• Language: English
• Published: Springer US 2017
• Subjects: QA75 Electronic computers. Computer science
• Online Access: http://umpir.ump.edu.my/id/eprint/18294/1/10.1007%252Fs11042-017-4999-9.pdf; http://umpir.ump.edu.my/id/eprint/18294/; https://doi.org/10.1007/s11042-017-4999-9

Image compression leads to minimize the storage-requirement of an image by reducing the size of the image. This paper presents a bit allocation strategy based on psychovisual threshold in image compression considering a similar idea of audio coding. In the audio coding, a dynamic bit allocation to each signal is related to the concept of variable block coding and bit allocation is performed on either a short block or long block of sample signals. Similarity, in our technique, more bits are assigned to a local block with visually-significant low frequency order, and fewer, with visually-insignificant high frequency order. This paper presents a bit allocation strategy based on psychovisual threshold in image compression. A psychovisual threshold is developed by minimizing the visual impact on the image quality degradation in image frequency coding. This paper investigates the error generated by the discrete cosine transform and sets the maximum acceptable error as a psychovisual threshold. The average reconstruction error per pixel on frequency order is utilized to prescribe a set of bit allocations which provide a significant improvement on the quality of image reconstruction at relatively low bit rates. The experimental results show that our dynamic bit-allocation technique in image compression manages to overcome artifact images in the image output. The proposed bit allocation strategy improves the quality of image reconstruction by about 20% compared to JPEG compression. This bit allocation strategy is designed to replace the traditional role of the quantization process in image compression.