Issue with convolution kernels that add up to zero - c++

Question

I'm making an image editing program in c++ using sfml and tried to add image filters using:
int clamp(int value, int min, int max)
{
if (value < min)
return min;
if (value > max)
return max;
return value;
}
void MyImage::applyKernel(std::vector<std::vector<int>> kernel)
{
int index(0), tempx(0), tempy(0);
int wr(0), wg(0), wb(0), wa(0), sum(0);
auto newPixels = new sf::Uint8[this->size_y * this->size_x * 4];
// Calculate the sum of the kernel
for (int i = 0; i < kernel.size(); i++) {
for (int j = 0; j < kernel[i].size(); j++) {
sum += kernel[i][j];
}
}
for (int y = 0; y < this->size_y; y++) {
for (int x = 0; x < this->size_x; x++) {
/*
Calculate weighted sum from kernel
*/
wr = wg = wb = wa = 0;
for (int i = 0; i < kernel.size(); i++) {
for (int j = 0; j < kernel[i].size(); j++) {
/*
Calculates the coordinates of the kernel relative to the pixel we are changing
*/
tempx = x + (j - floor(kernel[i].size() / 2));
tempy = y + (i - floor(kernel.size() / 2));
//std::cout << "kernel=(" << j << ", " << i << "), pixel=(" << x << ", " << y << ") tempPos=(" << tempx << ", " << tempy << ")\n";
/*
This code below should have the effect of mirroring the image in the case the kernel coordinate is out of bounds (along the edge of the image)
*/
tempx = (tempx < 0) ? -1 * tempx : tempx;
tempy = (tempy < 0) ? -1 * tempy : tempy;
tempx = (tempx > this->size_x) ? x - (j - floor(kernel[i].size() / 2)) : tempx;
tempy = (tempy > this->size_y) ? y - (i - floor(kernel.size() / 2)) : tempy;
if (tempx >= 0 && tempx < this->size_x && tempy >= 0 && tempy < this->size_y) {
index = (((tempy * this->size_x) - tempy) + (tempx)) * 4;
wr += kernel[i][j] * this->pixels[index];
wg += kernel[i][j] * this->pixels[index + 1];
wb += kernel[i][j] * this->pixels[index + 2];
wa += kernel[i][j] * this->pixels[index + 3];
}
}
}
if (sum) {
wr /= sum;
wg /= sum;
wb /= sum;
wa /= sum;
}
index = (((y * this->size_x) - y) + (x)) * 4;
newPixels[index] = clamp(wr, 0, 255); // Red
newPixels[index + 1] = clamp(wg, 0, 255); // Green
newPixels[index + 2] = clamp(wb, 0, 255); // Blue
newPixels[index + 3] = clamp(wa, 0, 255); // Alpha
}
}
this->pixels = newPixels;
// Copies the data from our sf::Uint8 array to the image object to be displayed => Removes the overhead of calling setPixel(x,y,color) for every pixel {As a side note setPixel() should always be avoided}|
this->im->create(this->size_x, this->size_y, this->pixels);
}
I was trying to use [-1,-1,-1], [-1,8,-1]. [-1,-1,-1] for edge detection but just ended up with a white image except for some pixels near the bottom. I've tried different images and kernels out but any that add to 0 don't work. For example if I take the edge detection kernel above and change the 8 to a 9, it gives an expected result. Is there something wrong with my idea of how convolution kernels work or is it just a bug in my code?
Thank you.