Avoiding boundaries if-cases when filtering image matrix

I have the following MATLAB Code which I want to optimize.
It's related to an image matrix (2D) which I want to filter.
Though it is MATLAB code, the same problem would arise in C code.

The problem is that I'm trying to access neighbors of the pixel which might cause problems at the boundaries of the image matrix.

vWeightsCoeff = zeros((2 * numRows * numCols), 1);

weightsIdx = -3;

% Filteration
for iColIdx = 1:numCols
    for iRowIdx = 1:numRows
        if(mod((iRowIdx + iColIdx), 2) == 0)
            continue;
        end

        weightsIdx = weightsIdx + 4;

        refPixel = mOutputImage(iRowIdx, iColIdx);

        if(iRowIdx < numRows)
            relPixel1 = mOutputImage((iRowIdx + 1), iColIdx);
            relWeight1 = vRangeTable(round((refPixel - relPixel1) * RANGE_RESOLUTION) + RANGE_CENTER_IDX);
        else
            relPixel1 = 0;
            relWeight1 = 0;
        end

        if(iRowIdx > 1)
            relPixel2 = mOutputImage((iRowIdx - 1), iColIdx);
            relWeight2 = vRangeTable(round((refPixel - relPixel2) * RANGE_RESOLUTION) + RANGE_CENTER_IDX);
        else
            relPixel2 = 0;
            relWeight2 = 0;
        end

        if(iColIdx < numCols)
            relPixel3 = mOutputImage(iRowIdx, (iColIdx + 1));
            relWeight3 = vRangeTable(round((refPixel - relPixel3) * RANGE_RESOLUTION) + RANGE_CENTER_IDX);
        else
            relPixel3 = 0;
            relWeight3 = 0;
        end

        if(iColIdx > 1)
            relPixel4 = mOutputImage(iRowIdx, (iColIdx - 1));
            relWeight4 = vRangeTable(round((refPixel - relPixel4) * RANGE_RESOLUTION) + RANGE_CENTER_IDX);
        else
            relPixel4 = 0;
            relWeight4 = 0;
        end

        weightsNormalizationFactor = PREDICT_NORMALIZATION_FACTOR / (relWeight1 + relWeight2 + relWeight3 + relWeight4);

        relWeight1 = relWeight1 * weightsNormalizationFactor;
        relWeight2 = relWeight2 * weightsNormalizationFactor;
        relWeight3 = relWeight3 * weightsNormalizationFactor;
        relWeight4 = relWeight4 * weightsNormalizationFactor;

        mOutputImage(iRowIdx, iColIdx) = mOutputImage(iRowIdx, iColIdx) - ((relWeight1 * relPixel1) + (relWeight2 * relPixel2) + (relWeight3 * relPixel3)+ (relWeight4 * relPixel4));

        vWeightsCoeff(weightsIdx:(weightsIdx + 3)) = [relWeight1; relWeight2; relWeight3; relWeight4];

    end
end

Just to clarify the variables:

• mOutputImage is the image matrix.
• numCols and numRows are the matrix dimensions.
• vWeightsCoeff is the vector of the weights.

Since each pixel is related to 4 others yet working only on half the pixels its size is 2 times the number of pixels.

Now, the questions are:

1. Can I do something smart to go over the same pixels yet skip the first if which works like dividing the pixels as in chess board (White Black Board)?
2. Can I do something to avoid the if which secures I'm not stepping out of boundaries and yet go through the same pixels?

If someone comes which a completely different arrangement I will be open for that as well.