Abstract
The author offers a power-efficient multichannel low-pass filter for digital image processing based on the cascade multiple accumulate finite impulse response (CMFIR) structure in this study. The CMFIR filter was created using the outputs of a linear time-invariant system (LTI), which was built using a cascaded integrator comb (CIC) and a MAC low-pass filter. The sample rate convertor based on CIC filters effectively conducts decimation or interpolation. The sample rate convertor with the CIC filter can only accommodate narrowband transmissions and so cannot be utilized for wideband signals. The MAC architecture-based sample rate convertor is a good solution for high-bandwidth signals, but it uses more resources like registers and flip-flops, which increases power consumption. Here, the CMFIR low-pass filter acts as an interpolator, introducing a sample to boost the image's resolution. CMFIR is a useful tool for addressing the issue of aliasing during sampling. In addition, the genetic algorithm was used to increase the filter's resource utilization and power consumption efficiency.
Highlights
Digital image processing applications are indicated in many areas of the present world [8, 24] such as medicine, automotive applications, geo engineering, industrial applications.The filtering technique is a part of the normal image enhancement process
The cascade multiple accumulate finite impulse response (CMFIR) filter is the combination of cascaded integrator comb (CIC) FIR and MAC FIR filters incorporating promising features of both filters [35]
Investigation indicated that the proposed CMFIR solution ensures higher static power consumption efficiency, dynamic power consumption efficiency, total power consumption efficiency, register utilization efficiency, LUT utilization efficiency, LUT-flip flop pairs utilization efficiency than MAC and CIC structure
Summary
The filtering technique is a part of the normal image enhancement process. It helps in solving problems of the image display [10] and, enables the improvement of image quality. One of the challenges is to remove noise from images [16, 32]. There is a need to develop a sample converter that works as a low-pass filter to remove the noise from images at low power consumption [13, 26]
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