Design for Implementation of Image Processing Algorithms



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Design for Implementation of Image Processing Algorithms dsertarsiay

4.3
 
General Applicability of the Proposed Methodology 
The major benefit of the DFI methodology is that it is ultimately flexible in nature.
As algorithm developers likely have their own design process based upon experience, it 
was imperative to propose a design methodology that could be used as an addendum to 
their current processes. This allows the methodology to be applied to algorithms that have 
already been designed, as well as algorithms that are currently in development. Once a 
developer has been introduced to the concepts of designing for implementation, it is likely 
that many of the guidelines will be taken into account as supplemental procedures during 
their own design process.
An additional benefit of the methodology is that it is inherently an iterative process, 
meaning that multiple iterations of its application to an algorithm will eventually converge 
to an optimal solution. This concept, however, also presents a potential pitfall. As has 
been mentioned previously in this work, different aspects of an image processing algorithm 


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can contribute differently to overall image quality [8], but also impact other design 
parameters. Elaborating further, an inexperienced developer could spend the majority of 
their time attempting to optimize a portion of the algorithm that won’t result in a noticeable 
reduction in execution time, logic utilization, or power consumption. For this reason, a 
method of analyzing the savings attributed to the different guidelines presented in the 
previous section would be useful. This could be done with a type of cost-table solution for 
different transforms and guidelines, but such an addition would be done as future research 
and would require the application of this methodology on a variety of image processing 
algorithms.
The flexibility of this methodology provides potential for it to be applied in other 
areas of digital implementation. Although the proposed methodology was designed with 
image processing algorithms in mind, a majority of the concepts presented in the guidelines 
are applicable to any type of digital processing algorithm that needs to be implemented in 
hardware, such as any DSP algorithms. Before it could be applied to other fields, however, 
a tolerance for error would need to be defined specific to the application desired. That is, 
a parameter that is analogous to image quality in this work would need to be identified.


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