## 3 Selection of Methods for Methodology
### Method for Criteria Weights  
Once the set of criteria is determined, the next step is to decide on their relative importance through weighting methods. The evaluation of criteria weights is a common issue that arises in many MCDM methods. Criteria weighting must be carefully selected in most MCDM models because it greatly affects the final ranking of the alternatives [51]. Weights can be specified by experts (subjective weighting) or calculated via mathematical weighing procedures (objective weighting). In objective weighting, the decision maker has no role in assigning the weights. Using an integrated weighting approach combining subjective and objective weighting methods is also possible. Objective weighting is applied once the data of the decision matrix is known, while subjective weighting can be applied once the criteria set is known. Depending on the characteristics of the decision problem, the available data, and the goals of decision-makers, numerous weighting methods can be used with MCDM.  
The stepwise weight assessment ratio analysis method (SWARA) [52] incorporates individual expert opinions, and it belongs to the subjective weighting method group. Naturally, these methods may require significant time and preparation for participants to evaluate the image content. This can be a drawback, especially when dealing with a large set of subjective criteria, and objective weighting may be more efficient. The entropy weight method (EWM) [53] is a commonly employed objective weighting method for MCDM problems, which evaluates the degree of value dispersion in decision-making. In contrast to subjective weighting models, the EWM's primary strength is its ability to eliminate the influence of human factors on indicator weights. However, in certain situations, EWM may also lead to distorted decision-making results.  
The SWARA method, which was selected for calculating criteria weights, can be summarized by the following six steps:  
1. Identification of the criteria set. This involves defining and selecting the key factors or attributes that are relevant and important to the decision-making problem at hand. The criteria must be clearly defined, measurable, and non-redundant.
2. An expert evaluation is used to sort the criteria in descending order based on their importance. This step provides a starting point for determining the criteria weights. Ten experts consisting of scientists from Vilnius Gediminas Technical University (Vilnius Tech) with teaching experience in image processing were interviewed to rank the criteria.
3. Determining the average value of comparative importance \(s_{j}\); how much more important is criteria \(C_{i}\) than criteria \(C_{i+1}\). The results are presented in Table 1.
4. The benefits of the comparative importance are calculated as follows: \[k_{j}=\left\{\begin{aligned} & 1,& j=1,\\ & s_{j}+1,& j>1.\end{aligned}\right.\] (6)(5) Transitional weights are recalculated, where \(j\) is the index of the criteria:  
\[q_{j}=\begin{cases}1,&j=1,\\ \frac{q_{j-1}}{k_{j}},&j>1.\end{cases} \tag{7}\]  
(6) The final weights are normalized, where \(n\) is the number of criteria:  
\[w_{j}=\frac{q_{j}}{\sum_{j=1}^{n}q_{j}} \tag{8}\]  
The results are presented in the last column of Table 2.  
Average values of comparative importance \(s_{j}\) are then used for calculating final criteria weights \(w_{j}\) by the SWARA method (Table 2).